1 code implementation • ECCV 2020 • Deng-Ping Fan, Yingjie Zhai, Ali Borji, Jufeng Yang, Ling Shao
In particular, we 1) propose a bifurcated backbone strategy (BBS) to split the multi-level features into teacher and student features, and 2) utilize a depth-enhanced module (DEM) to excavate informative parts of depth cues from the channel and spatial views.
1 code implementation • 2 Apr 2024 • Cheng Gong, Haoshuai Zheng, Mengting Hu, Zheng Lin, Deng-Ping Fan, Yuzhi Zhang, Tao Li
Quantization is a promising method that reduces memory usage and computational intensity of Deep Neural Networks (DNNs), but it often leads to significant output error that hinder model deployment.
1 code implementation • 30 Mar 2024 • Pancheng Zhao, Peng Xu, Pengda Qin, Deng-Ping Fan, Zhicheng Zhang, Guoli Jia, BoWen Zhou, Jufeng Yang
Camouflaged vision perception is an important vision task with numerous practical applications.
1 code implementation • 11 Mar 2024 • Guobao Xiao, Jun Yu, Jiayi Ma, Deng-Ping Fan, Ling Shao
The principle of LSC is to preserve the latent semantic consensus in both data points and model hypotheses.
no code implementations • 7 Mar 2024 • Yao Jiang, Xinyu Yan, Ge-Peng Ji, Keren Fu, Meijun Sun, Huan Xiong, Deng-Ping Fan, Fahad Shahbaz Khan
This paper endeavors to evaluate the competency of popular LVLMs in specialized and general tasks, respectively, aiming to offer a comprehensive understanding of these novel models.
1 code implementation • 27 Jan 2024 • Diandian Guo, Deng-Ping Fan, Tongyu Lu, Christos Sakaridis, Luc van Gool
The estimation of implicit cross-frame correspondences and the high computational cost have long been major challenges in video semantic segmentation (VSS) for driving scenes.
1 code implementation • 7 Jan 2024 • Peng Zheng, Dehong Gao, Deng-Ping Fan, Li Liu, Jorma Laaksonen, Wanli Ouyang, Nicu Sebe
It comprises two essential components: the localization module (LM) and the reconstruction module (RM) with our proposed bilateral reference (BiRef).
Ranked #1 on Camouflaged Object Segmentation on COD
Camouflaged Object Segmentation Dichotomous Image Segmentation +3
1 code implementation • 4 Jan 2024 • Yiran Song, Qianyu Zhou, Xiangtai Li, Deng-Ping Fan, Xuequan Lu, Lizhuang Ma
To this end, we propose Scalable Bias-Mode Attention Mask (BA-SAM) to enhance SAM's adaptability to varying image resolutions while eliminating the need for structure modifications.
no code implementations • 28 Nov 2023 • Shupeng Cheng, Ge-Peng Ji, Pengda Qin, Deng-Ping Fan, BoWen Zhou, Peng Xu
Our motivation is to make full use of the semantic intelligence and intrinsic knowledge of recent Multimodal Large Language Models (MLLMs) to decompose this complex task in a human-like way.
1 code implementation • 25 Nov 2023 • Ziyang Luo, Nian Liu, Wangbo Zhao, Xuguang Yang, Dingwen Zhang, Deng-Ping Fan, Fahad Khan, Junwei Han
Salient object detection (SOD) and camouflaged object detection (COD) are related yet distinct binary mapping tasks.
1 code implementation • 23 Oct 2023 • Yu-Cheng Chou, Bowen Li, Deng-Ping Fan, Alan Yuille, Zongwei Zhou
In summary, this research proposes an efficient annotation strategy for tumor detection and localization that is less accurate than per-pixel annotations but useful for creating large-scale datasets for screening tumors in various medical modalities.
no code implementations • 19 Sep 2023 • Tao Zhou, Yizhe Zhang, Geng Chen, Yi Zhou, Ye Wu, Deng-Ping Fan
Besides, a Scale-aware Convolution Module (SCM) is proposed to learn scale-aware features by using dilated convolutions with different ratios, in order to effectively deal with scale variation.
no code implementations • 16 Aug 2023 • Han Zhou, Dong Ni, Ao Chang, Xinrui Zhou, Rusi Chen, Yanlin Chen, Lian Liu, Jiamin Liang, Yuhao Huang, Tong Han, Zhe Liu, Deng-Ping Fan, Xin Yang
Second, to better preserve the integrity and textural information of US images, we implemented a dual-decoder that decouples the content and textural features in the generator.
1 code implementation • 30 Jul 2023 • Debesh Jha, Vanshali Sharma, Debapriya Banik, Debayan Bhattacharya, Kaushiki Roy, Steven A. Hicks, Nikhil Kumar Tomar, Vajira Thambawita, Adrian Krenzer, Ge-Peng Ji, Sahadev Poudel, George Batchkala, Saruar Alam, Awadelrahman M. A. Ahmed, Quoc-Huy Trinh, Zeshan Khan, Tien-Phat Nguyen, Shruti Shrestha, Sabari Nathan, Jeonghwan Gwak, Ritika K. Jha, Zheyuan Zhang, Alexander Schlaefer, Debotosh Bhattacharjee, M. K. Bhuyan, Pradip K. Das, Deng-Ping Fan, Sravanthi Parsa, Sharib Ali, Michael A. Riegler, Pål Halvorsen, Thomas de Lange, Ulas Bagci
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps.
1 code implementation • 27 Jul 2023 • Haotong Qin, Ge-Peng Ji, Salman Khan, Deng-Ping Fan, Fahad Shahbaz Khan, Luc van Gool
Google's Bard has emerged as a formidable competitor to OpenAI's ChatGPT in the field of conversational AI.
1 code implementation • 16 Jul 2023 • Jialun Pei, Tao Jiang, He Tang, Nian Liu, Yueming Jin, Deng-Ping Fan, Pheng-Ann Heng
We propose a novel approach for RGB-D salient instance segmentation using a dual-branch cross-modal feature calibration architecture called CalibNet.
1 code implementation • 13 Jun 2023 • Xuying Zhang, Bowen Yin, Zheng Lin, Qibin Hou, Deng-Ping Fan, Ming-Ming Cheng
We consider the problem of referring camouflaged object detection (Ref-COD), a new task that aims to segment specified camouflaged objects based on a small set of referring images with salient target objects.
1 code implementation • 6 Jun 2023 • Lian Liu, Han Zhou, Jiongquan Chen, Sijing Liu, Wenlong Shi, Dong Ni, Deng-Ping Fan, Xin Yang
Deep neural networks have been widely applied in dichotomous medical image segmentation (DMIS) of many anatomical structures in several modalities, achieving promising performance.
no code implementations • 26 May 2023 • Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piękos, Aditya Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanić, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber
What should be the social structure of an NLSOM?
2 code implementations • 23 May 2023 • Guotao Wang, Chenglizhao Chen, Aimin Hao, Hong Qin, Deng-Ping Fan
The main reason is that there always exist "blind zooms" when using HMD to collect fixations since the users cannot keep spinning their heads to explore the entire panoptic scene all the time.
1 code implementation • 28 Apr 2023 • Yuhao Huang, Xin Yang, Lian Liu, Han Zhou, Ao Chang, Xinrui Zhou, Rusi Chen, Junxuan Yu, Jiongquan Chen, Chaoyu Chen, Sijing Liu, Haozhe Chi, Xindi Hu, Kejuan Yue, Lei LI, Vicente Grau, Deng-Ping Fan, Fajin Dong, Dong Ni
To fully validate SAM's performance on medical data, we collected and sorted 53 open-source datasets and built a large medical segmentation dataset with 18 modalities, 84 objects, 125 object-modality paired targets, 1050K 2D images, and 6033K masks.
1 code implementation • CVPR 2023 • Guolei Sun, Zhaochong An, Yun Liu, Ce Liu, Christos Sakaridis, Deng-Ping Fan, Luc van Gool
We further advance the frontier of this field by systematically studying a new challenge named indiscernible object counting (IOC), the goal of which is to count objects that are blended with respect to their surroundings.
1 code implementation • 21 Apr 2023 • Deng-Ping Fan, Ge-Peng Ji, Peng Xu, Ming-Ming Cheng, Christos Sakaridis, Luc van Gool
Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive objects exhibiting camouflage.
no code implementations • 12 Apr 2023 • Ge-Peng Ji, Deng-Ping Fan, Peng Xu, Ming-Ming Cheng, BoWen Zhou, Luc van Gool
Segmenting anything is a ground-breaking step toward artificial general intelligence, and the Segment Anything Model (SAM) greatly fosters the foundation models for computer vision.
1 code implementation • 11 Apr 2023 • Xue-Jing Luo, Shuo Wang, Zongwei Wu, Christos Sakaridis, Yun Cheng, Deng-Ping Fan, Luc van Gool
Specifically, we leverage the latent diffusion model to synthesize salient objects in camouflaged scenes, while using the zero-shot image classification ability of the Contrastive Language-Image Pre-training (CLIP) model to prevent synthesis failures and ensure the synthesized object aligns with the input prompt.
no code implementations • 2 Feb 2023 • Weimin Shi, Mingchen Zhuge, Dehong Gao, Zhong Zhou, Ming-Ming Cheng, Deng-Ping Fan
Daily images may convey abstract meanings that require us to memorize and infer profound information from them.
1 code implementation • ICCV 2023 • Zongwei Wu, Danda Pani Paudel, Deng-Ping Fan, Jingjing Wang, Shuo Wang, Cédric Demonceaux, Radu Timofte, Luc van Gool
In this work, we adapt such depth inference models for object segmentation using the objects' "pop-out" prior in 3D.
1 code implementation • 10 Dec 2022 • Bowen Yin, Xuying Zhang, Qibin Hou, Bo-Yuan Sun, Deng-Ping Fan, Luc van Gool
How to identify and segment camouflaged objects from the background is challenging.
1 code implementation • 27 Oct 2022 • Ge-Peng Ji, Mingcheng Zhuge, Dehong Gao, Deng-Ping Fan, Christos Sakaridis, Luc van Gool
We present a masked vision-language transformer (MVLT) for fashion-specific multi-modal representation.
1 code implementation • 5 Jul 2022 • Jialun Pei, Tianyang Cheng, Deng-Ping Fan, He Tang, Chuanbo Chen, Luc van Gool
We present OSFormer, the first one-stage transformer framework for camouflaged instance segmentation (CIS).
2 code implementations • 30 May 2022 • Peng Zheng, Huazhu Fu, Deng-Ping Fan, Qi Fan, Jie Qin, Yu-Wing Tai, Chi-Keung Tang, Luc van Gool
In this paper, we present a novel end-to-end group collaborative learning network, termed GCoNet+, which can effectively and efficiently (250 fps) identify co-salient objects in natural scenes.
Ranked #1 on Co-Salient Object Detection on CoCA
1 code implementation • 25 May 2022 • Ge-Peng Ji, Deng-Ping Fan, Yu-Cheng Chou, Dengxin Dai, Alexander Liniger, Luc van Gool
This paper introduces DGNet, a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD).
1 code implementation • 23 May 2022 • Yunqiu Lv, Jing Zhang, Yuchao Dai, Aixuan Li, Nick Barnes, Deng-Ping Fan
With the above understanding about camouflaged objects, we present the first triple-task learning framework to simultaneously localize, segment, and rank camouflaged objects, indicating the conspicuousness level of camouflage.
4 code implementations • 27 Mar 2022 • Ge-Peng Ji, Guobao Xiao, Yu-Cheng Chou, Deng-Ping Fan, Kai Zhao, Geng Chen, Luc van Gool
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era.
Ranked #2 on Video Polyp Segmentation on SUN-SEG-Easy (Unseen)
2 code implementations • 24 Mar 2022 • Kai Zhang, Yawei Li, Jingyun Liang, JieZhang Cao, Yulun Zhang, Hao Tang, Deng-Ping Fan, Radu Timofte, Luc van Gool
While recent years have witnessed a dramatic upsurge of exploiting deep neural networks toward solving image denoising, existing methods mostly rely on simple noise assumptions, such as additive white Gaussian noise (AWGN), JPEG compression noise and camera sensor noise, and a general-purpose blind denoising method for real images remains unsolved.
Ranked #1 on Image Denoising on urban100 sigma15
1 code implementation • CVPR 2022 • Xuelian Cheng, Huan Xiong, Deng-Ping Fan, Yiran Zhong, Mehrtash Harandi, Tom Drummond, ZongYuan Ge
We propose a new video camouflaged object detection (VCOD) framework that can exploit both short-term dynamics and long-term temporal consistency to detect camouflaged objects from video frames.
Ranked #2 on Camouflaged Object Segmentation on Camouflaged Animal Dataset (using extra training data)
1 code implementation • 6 Mar 2022 • Xuebin Qin, Hang Dai, Xiaobin Hu, Deng-Ping Fan, Ling Shao, and Luc Van Gool
We present a systematic study on a new task called dichotomous image segmentation (DIS) , which aims to segment highly accurate objects from natural images.
Ranked #5 on Dichotomous Image Segmentation on DIS-TE1
3 code implementations • 31 Dec 2021 • Deng-Ping Fan, Ziling Huang, Peng Zheng, Hong Liu, Xuebin Qin, Luc van Gool
Besides, we elaborate comprehensive experiments on the existing 19 cutting-edge models.
1 code implementation • 27 Dec 2021 • Guotao Wang, Chenglizhao Chen, Deng-Ping Fan, Aimin Hao, Hong Qin
Moreover, we distill knowledge from these regions to obtain complete new spatial-temporal-audio (STA) fixation prediction (FP) networks, enabling broad applications in cases where video tags are not available.
1 code implementation • 13 Oct 2021 • Jing Zhang, Yuchao Dai, Mochu Xiang, Deng-Ping Fan, Peyman Moghadam, Mingyi He, Christian Walder, Kaihao Zhang, Mehrtash Harandi, Nick Barnes
Deep neural networks can be roughly divided into deterministic neural networks and stochastic neural networks. The former is usually trained to achieve a mapping from input space to output space via maximum likelihood estimation for the weights, which leads to deterministic predictions during testing.
no code implementations • 29 Sep 2021 • Xuelian Cheng, Huan Xiong, Deng-Ping Fan, Yiran Zhong, Mehrtash Harandi, Tom Drummond, ZongYuan Ge
The proposed SLT-Net leverages on both short-term dynamics and long-term temporal consistency to detect concealed objects in continuous video frames.
1 code implementation • ICCV 2021 • Jing Zhang, Deng-Ping Fan, Yuchao Dai, Xin Yu, Yiran Zhong, Nick Barnes, Ling Shao
In this paper, we introduce a novel multi-stage cascaded learning framework via mutual information minimization to "explicitly" model the multi-modal information between RGB image and depth data.
3 code implementations • ICCV 2021 • Tao Zhou, Deng-Ping Fan, Geng Chen, Yi Zhou, Huazhu Fu
To effectively fuse cross-modal features in the shared learning network, we propose a cross-enhanced integration module (CIM) and then propagate the fused feature to the next layer for integrating cross-level information.
2 code implementations • 16 Aug 2021 • Bo Dong, Wenhai Wang, Deng-Ping Fan, Jinpeng Li, Huazhu Fu, Ling Shao
Unlike existing CNN-based methods, we adopt a transformer encoder, which learns more powerful and robust representations.
Ranked #9 on Medical Image Segmentation on CVC-ColonDB
1 code implementation • ICCV 2021 • Ge-Peng Ji, Deng-Ping Fan, Keren Fu, Zhe Wu, Jianbing Shen, Ling Shao
Previous video object segmentation approaches mainly focus on using simplex solutions between appearance and motion, limiting feature collaboration efficiency among and across these two cues.
Ranked #7 on Video Polyp Segmentation on SUN-SEG-Hard (Unseen)
16 code implementations • 25 Jun 2021 • Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, Ling Shao
We hope this work will facilitate state-of-the-art Transformer researches in computer vision.
Ranked #23 on Object Detection on COCO-O
1 code implementation • CVPR 2021 • Xin Li, Deng-Ping Fan, Fan Yang, Ao Luo, Hong Cheng, Zicheng Liu
We address this problem with the use of a novel Probabilistic Model Distillation (PMD) approach which transfers knowledge learned by a probabilistic teacher model on synthetic data to a static student model with the use of unlabeled real image pairs.
1 code implementation • CVPR 2021 • Guotao Wang, Chenglizhao Chen, Deng-Ping Fan, Aimin Hao, Hong Qin
Thanks to the rapid advances in the deep learning techniques and the wide availability of large-scale training sets, the performances of video saliency detection models have been improving steadily and significantly.
3 code implementations • 18 May 2021 • Ge-Peng Ji, Yu-Cheng Chou, Deng-Ping Fan, Geng Chen, Huazhu Fu, Debesh Jha, Ling Shao
Existing video polyp segmentation (VPS) models typically employ convolutional neural networks (CNNs) to extract features.
Ranked #6 on Video Polyp Segmentation on SUN-SEG-Easy (Unseen)
2 code implementations • 7 May 2021 • Deng-Ping Fan, Jing Zhang, Gang Xu, Ming-Ming Cheng, Ling Shao
This design bias has led to a saturation in performance for state-of-the-art SOD models when evaluated on existing datasets.
1 code implementation • CVPR 2021 • Haiyang Mei, Ge-Peng Ji, Ziqi Wei, Xin Yang, Xiaopeng Wei, Deng-Ping Fan
In this paper, we strive to embrace challenges towards effective and efficient COS. To this end, we develop a bio-inspired framework, termed Positioning and Focus Network (PFNet), which mimics the process of predation in nature.
Ranked #12 on Dichotomous Image Segmentation on DIS-TE3
Camouflaged Object Segmentation Dichotomous Image Segmentation +3
2 code implementations • 20 Apr 2021 • Yuxin Mao, Jing Zhang, Zhexiong Wan, Yuchao Dai, Aixuan Li, Yunqiu Lv, Xinyu Tian, Deng-Ping Fan, Nick Barnes
For the former, we apply transformer to a deterministic model, and explain that the effective structure modeling and global context modeling abilities lead to its superior performance compared with the CNN based frameworks.
1 code implementation • CVPR 2021 • Qiang Zhai, Xin Li, Fan Yang, Chenglizhao Chen, Hong Cheng, Deng-Ping Fan
Automatically detecting/segmenting object(s) that blend in with their surroundings is difficult for current models.
1 code implementation • CVPR 2021 • Mingchen Zhuge, Dehong Gao, Deng-Ping Fan, Linbo Jin, Ben Chen, Haoming Zhou, Minghui Qiu, Ling Shao
We present a new vision-language (VL) pre-training model dubbed Kaleido-BERT, which introduces a novel kaleido strategy for fashion cross-modality representations from transformers.
1 code implementation • CVPR 2021 • Qi Fan, Deng-Ping Fan, Huazhu Fu, Chi Keung Tang, Ling Shao, Yu-Wing Tai
We present a novel group collaborative learning framework (GCoNet) capable of detecting co-salient objects in real time (16ms), by simultaneously mining consensus representations at group level based on the two necessary criteria: 1) intra-group compactness to better formulate the consistency among co-salient objects by capturing their inherent shared attributes using our novel group affinity module; 2) inter-group separability to effectively suppress the influence of noisy objects on the output by introducing our new group collaborating module conditioning the inconsistent consensus.
Ranked #5 on Co-Salient Object Detection on CoCA
1 code implementation • CVPR 2021 • Yunqiu Lv, Jing Zhang, Yuchao Dai, Aixuan Li, Bowen Liu, Nick Barnes, Deng-Ping Fan
With the above understanding about camouflaged objects, we present the first ranking based COD network (Rank-Net) to simultaneously localize, segment and rank camouflaged objects.
9 code implementations • ICCV 2021 • Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, Ling Shao
Unlike the recently-proposed Transformer model (e. g., ViT) that is specially designed for image classification, we propose Pyramid Vision Transformer~(PVT), which overcomes the difficulties of porting Transformer to various dense prediction tasks.
Ranked #5 on Semantic Segmentation on SynPASS
1 code implementation • 20 Feb 2021 • Deng-Ping Fan, Ge-Peng Ji, Ming-Ming Cheng, Ling Shao
We present the first systematic study on concealed object detection (COD), which aims to identify objects that are "perfectly" embedded in their background.
Ranked #5 on Camouflaged Object Segmentation on CHAMELEON
Camouflaged Object Segmentation Dichotomous Image Segmentation +2
3 code implementations • 19 Jan 2021 • Mingchen Zhuge, Deng-Ping Fan, Nian Liu, Dingwen Zhang, Dong Xu, Ling Shao
We define the concept of integrity at both a micro and macro level.
5 code implementations • 12 Jan 2021 • Xuebin Qin, Deng-Ping Fan, Chenyang Huang, Cyril Diagne, Zichen Zhang, Adrià Cabeza Sant'Anna, Albert Suàrez, Martin Jagersand, Ling Shao
In this paper, we propose a simple yet powerful Boundary-Aware Segmentation Network (BASNet), which comprises a predict-refine architecture and a hybrid loss, for highly accurate image segmentation.
1 code implementation • ICCV 2021 • Fan Yang, Qiang Zhai, Xin Li, Rui Huang, Ao Luo, Hong Cheng, Deng-Ping Fan
Spotting objects that are visually adapted to their surroundings is challenging for both humans and AI.
1 code implementation • 10 Oct 2020 • Keren Fu, Yao Jiang, Ge-Peng Ji, Tao Zhou, Qijun Zhao, Deng-Ping Fan
Secondly, we benchmark nine representative light field SOD models together with several cutting-edge RGB-D SOD models on four widely used light field datasets, from which insightful discussions and analyses, including a comparison between light field SOD and RGB-D SOD models, are achieved.
4 code implementations • 7 Sep 2020 • Jing Zhang, Deng-Ping Fan, Yuchao Dai, Saeed Anwar, Fatemeh Saleh, Sadegh Aliakbarian, Nick Barnes
Our framework includes two main models: 1) a generator model, which maps the input image and latent variable to stochastic saliency prediction, and 2) an inference model, which gradually updates the latent variable by sampling it from the true or approximate posterior distribution.
Ranked #1 on RGB-D Salient Object Detection on LFSD
2 code implementations • 26 Aug 2020 • Keren Fu, Deng-Ping Fan, Ge-Peng Ji, Qijun Zhao, Jianbing Shen, Ce Zhu
Inspired by the observation that RGB and depth modalities actually present certain commonality in distinguishing salient objects, a novel joint learning and densely cooperative fusion (JL-DCF) architecture is designed to learn from both RGB and depth inputs through a shared network backbone, known as the Siamese architecture.
Ranked #3 on RGB-D Salient Object Detection on STERE
9 code implementations • 1 Aug 2020 • Tao Zhou, Deng-Ping Fan, Ming-Ming Cheng, Jianbing Shen, Ling Shao
Further, considering that the light field can also provide depth maps, we review SOD models and popular benchmark datasets from this domain as well.
2 code implementations • 7 Jul 2020 • Deng-Ping Fan, Tengpeng Li, Zheng Lin, Ge-Peng Ji, Dingwen Zhang, Ming-Ming Cheng, Huazhu Fu, Jianbing Shen
CoSOD is an emerging and rapidly growing extension of salient object detection (SOD), which aims to detect the co-occurring salient objects in a group of images.
Ranked #7 on Co-Salient Object Detection on CoCA
2 code implementations • 6 Jul 2020 • Yingjie Zhai, Deng-Ping Fan, Jufeng Yang, Ali Borji, Ling Shao, Junwei Han, Liang Wang
In particular, first, we propose to regroup the multi-level features into teacher and student features using a bifurcated backbone strategy (BBS).
Ranked #2 on RGB-D Salient Object Detection on RGBD135
4 code implementations • 13 Jun 2020 • Deng-Ping Fan, Ge-Peng Ji, Tao Zhou, Geng Chen, Huazhu Fu, Jianbing Shen, Ling Shao
To address these challenges, we propose a parallel reverse attention network (PraNet) for accurate polyp segmentation in colonoscopy images.
Ranked #7 on Video Polyp Segmentation on SUN-SEG-Easy (Unseen)
2 code implementations • CVPR 2020 • Deng-Ping Fan, Ge-Peng Ji, Guolei Sun, Ming-Ming Cheng, Jianbing Shen, Ling Shao
We present a comprehensive study on a new task named camouflaged object detection (COD), which aims to identify objects that are "seamlessly" embedded in their surroundings.
Ranked #10 on Camouflaged Object Segmentation on CAMO
1 code implementation • CVPR 2020 • Deng-Ping Fan, Zheng Lin, Ge-Peng Ji, Dingwen Zhang, Huazhu Fu, Ming-Ming Cheng
Co-salient object detection (CoSOD) is a newly emerging and rapidly growing branch of salient object detection (SOD), which aims to detect the co-occurring salient objects in multiple images.
Ranked #2 on Co-Salient Object Detection on iCoSeg
1 code implementation • 30 Apr 2020 • Zhao Zhang, Zheng Lin, Jun Xu, Wenda Jin, Shao-Ping Lu, Deng-Ping Fan
To better explore salient information in both foreground and background regions, this paper proposes a Bilateral Attention Network (BiANet) for the RGB-D SOD task.
Ranked #3 on RGB-D Salient Object Detection on RGBD135
3 code implementations • 22 Apr 2020 • Deng-Ping Fan, Tao Zhou, Ge-Peng Ji, Yi Zhou, Geng Chen, Huazhu Fu, Jianbing Shen, Ling Shao
Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis.
1 code implementation • CVPR 2020 • Keren Fu, Deng-Ping Fan, Ge-Peng Ji, Qijun Zhao
This paper proposes a novel joint learning and densely-cooperative fusion (JL-DCF) architecture for RGB-D salient object detection.
Ranked #6 on RGB-D Salient Object Detection on NLPR
1 code implementation • 15 Apr 2020 • Yu-Huan Wu, Shang-Hua Gao, Jie Mei, Jun Xu, Deng-Ping Fan, Rong-Guo Zhang, Ming-Ming Cheng
The chest CT scan test provides a valuable complementary tool to the RT-PCR test, and it can identify the patients in the early-stage with high sensitivity.
1 code implementation • CVPR 2020 • Jing Zhang, Deng-Ping Fan, Yuchao Dai, Saeed Anwar, Fatemeh Sadat Saleh, Tong Zhang, Nick Barnes
In this paper, we propose the first framework (UCNet) to employ uncertainty for RGB-D saliency detection by learning from the data labeling process.
Ranked #4 on RGB-D Salient Object Detection on LFSD
1 code implementation • ICCV 2019 • Deng-Ping Fan, Shengchuan Zhang, Yu-Huan Wu, Yun Liu, Ming-Ming Cheng, Bo Ren, Paul L. Rosin, Rongrong Ji
In this paper, we design a perceptual metric, called Structure Co-Occurrence Texture (Scoot), which simultaneously considers the block-level spatial structure and co-occurrence texture statistics.
2 code implementations • 15 Jul 2019 • Deng-Ping Fan, Zheng Lin, Jia-Xing Zhao, Yun Liu, Zhao Zhang, Qibin Hou, Menglong Zhu, Ming-Ming Cheng
The use of RGB-D information for salient object detection has been extensively explored in recent years.
Ranked #4 on RGB-D Salient Object Detection on RGBD135
1 code implementation • CVPR 2019 • Deng-Ping Fan, Wenguan Wang, Ming-Ming Cheng, Jianbing Shen
This is the first work that explicitly emphasizes the challenge of saliency shift, i. e., the video salient object(s) may dynamically change.
Ranked #1 on Video Salient Object Detection on DAVSOD-Difficult20
1 code implementation • 14 May 2019 • Lin-Zhuo Chen, Xuan-Yi Li, Deng-Ping Fan, Kai Wang, Shao-Ping Lu, Ming-Ming Cheng
We design a novel Local Spatial Aware (LSA) layer, which can learn to generate Spatial Distribution Weights (SDWs) hierarchically based on the spatial relationship in local region for spatial independent operations, to establish the relationship between these operations and spatial distribution, thus capturing the local geometric structure sensitively. We further propose the LSANet, which is based on LSA layer, aggregating the spatial information with associated features in each layer of the network better in network design. The experiments show that our LSANet can achieve on par or better performance than the state-of-the-art methods when evaluating on the challenging benchmark datasets.
2 code implementations • 26 May 2018 • Deng-Ping Fan, Cheng Gong, Yang Cao, Bo Ren, Ming-Ming Cheng, Ali Borji
The existing binary foreground map (FM) measures to address various types of errors in either pixel-wise or structural ways.
1 code implementation • 9 Apr 2018 • Yun Liu, Ming-Ming Cheng, Deng-Ping Fan, Le Zhang, Jiawang Bian, DaCheng Tao
Semantic edge detection (SED), which aims at jointly extracting edges as well as their category information, has far-reaching applications in domains such as semantic segmentation, object proposal generation, and object recognition.
1 code implementation • 9 Apr 2018 • Deng-Ping Fan, Shengchuan Zhang, Yu-Huan Wu, Ming-Ming Cheng, Bo Ren, Rongrong Ji, Paul L. Rosin
However, human perception of the similarity of two sketches will consider both structure and texture as essential factors and is not sensitive to slight ("pixel-level") mismatches.
no code implementations • ECCV 2018 • Deng-Ping Fan, Ming-Ming Cheng, Jiang-Jiang Liu, Shang-Hua Gao, Qibin Hou, Ali Borji
Our analysis identifies a serious design bias of existing SOD datasets which assumes that each image contains at least one clearly outstanding salient object in low clutter.
1 code implementation • ICCV 2017 • Deng-Ping Fan, Ming-Ming Cheng, Yun Liu, Tao Li, Ali Borji
Our new measure simultaneously evaluates region-aware and object-aware structural similarity between a SM and a GT map.