no code implementations • 30 Mar 2024 • Xiaoyang Lyu, Yang-tian Sun, Yi-Hua Huang, Xiuzhe Wu, ZiYi Yang, Yilun Chen, Jiangmiao Pang, Xiaojuan Qi
In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate 3D reconstruction with intricate details while inheriting the high efficiency and rendering quality of 3DGS.
1 code implementation • 28 Mar 2024 • Bu Jin, Yupeng Zheng, Pengfei Li, Weize Li, Yuhang Zheng, Sujie Hu, Xinyu Liu, Jinwei Zhu, Zhijie Yan, Haiyang Sun, Kun Zhan, Peng Jia, Xiaoxiao Long, Yilun Chen, Hao Zhao
However, the exploration of 3D dense captioning in outdoor scenes is hindered by two major challenges: 1) the \textbf{domain gap} between indoor and outdoor scenes, such as dynamics and sparse visual inputs, makes it difficult to directly adapt existing indoor methods; 2) the \textbf{lack of data} with comprehensive box-caption pair annotations specifically tailored for outdoor scenes.
no code implementations • 25 Feb 2024 • Zhipeng Ma, Zheyan Tu, Xinhai Chen, Yan Zhang, Deguo Xia, Guyue Zhou, Yilun Chen, Yu Zheng, Jiangtao Gong
The experimental results demonstrate that JGRM outperforms existing methods in both road segment representation and trajectory representation tasks.
2 code implementations • 23 Feb 2024 • Zhe Wang, Siqi Fan, Xiaoliang Huo, Tongda Xu, Yan Wang, Jingjing Liu, Yilun Chen, Ya-Qin Zhang
In autonomous driving, cooperative perception makes use of multi-view cameras from both vehicles and infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint.
3 code implementations • 31 Aug 2023 • Runsen Xu, Xiaolong Wang, Tai Wang, Yilun Chen, Jiangmiao Pang, Dahua Lin
The unprecedented advancements in Large Language Models (LLMs) have shown a profound impact on natural language processing but are yet to fully embrace the realm of 3D understanding.
Ranked #3 on 3D Object Captioning on Objaverse
1 code implementation • 8 Aug 2023 • Yilun Chen, Zhiding Yu, Yukang Chen, Shiyi Lan, Animashree Anandkumar, Jiaya Jia, Jose Alvarez
For 3D object detection, we instantiate this method as FocalFormer3D, a simple yet effective detector that excels at excavating difficult objects and improving prediction recall.
Ranked #8 on 3D Object Detection on nuScenes
2 code implementations • 20 Mar 2023 • Zhe Wang, Siqi Fan, Xiaoliang Huo, Tongda Xu, Yan Wang, Jingjing Liu, Yilun Chen, Ya-Qin Zhang
In autonomous driving, Vehicle-Infrastructure Cooperative 3D Object Detection (VIC3D) makes use of multi-view cameras from both vehicles and traffic infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint.
1 code implementation • ICCV 2023 • Yilun Chen, Zhiding Yu, Yukang Chen, Shiyi Lan, Anima Anandkumar, Jiaya Jia, Jose M. Alvarez
For 3D object detection, we instantiate this method as FocalFormer3D, a simple yet effective detector that excels at excavating difficult objects and improving prediction recall.
1 code implementation • ICCV 2023 • Zhijie Yan, Pengfei Li, Zheng Fu, Shaocong Xu, Yongliang Shi, Xiaoxue Chen, Yuhang Zheng, Yang Li, Tianyu Liu, Chuxuan Li, Nairui Luo, Xu Gao, Yilun Chen, Zuoxu Wang, Yifeng Shi, Pengfei Huang, Zhengxiao Han, Jirui Yuan, Jiangtao Gong, Guyue Zhou, Hang Zhao, Hao Zhao
One of the most challenging problems in motion forecasting is interactive trajectory prediction, whose goal is to jointly forecasts the future trajectories of interacting agents.
1 code implementation • 2 Jun 2022 • Tao Hu, Shu Liu, Yilun Chen, Tiancheng Shen, Jiaya Jia
Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes.
1 code implementation • 1 Jun 2022 • Yanwei Li, Yilun Chen, Xiaojuan Qi, Zeming Li, Jian Sun, Jiaya Jia
To this end, the modality-specific space is first designed to represent different inputs in the voxel feature space.
1 code implementation • 6 Apr 2022 • Yilun Chen, Shijia Huang, Shu Liu, Bei Yu, Jiaya Jia
First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features.
1 code implementation • CVPR 2022 • Shijia Huang, Yilun Chen, Jiaya Jia, LiWei Wang
The multi-view space enables the network to learn a more robust multi-modal representation for 3D visual grounding and eliminates the dependence on specific views.
1 code implementation • CVPR 2022 • Xuyang Bai, Zeyu Hu, Xinge Zhu, Qingqiu Huang, Yilun Chen, Hongbo Fu, Chiew-Lan Tai
The attention mechanism of the transformer enables our model to adaptively determine where and what information should be taken from the image, leading to a robust and effective fusion strategy.
Ranked #3 on 3D Object Detection on nuScenes LiDAR only
no code implementations • CVPR 2022 • Tao Hu, Shu Liu, Yilun Chen, Tiancheng Shen, Jiaya Jia
Neural Radiance Fields (NeRF) has been wildly applied to various tasks for its high-quality representation of 3D scenes.
1 code implementation • 4 Jun 2021 • Tong Qin, Yuxin Zheng, Tongqing Chen, Yilun Chen, Qing Su
Finally, the semantic map is compressed and distributed to production cars, which use this map for localization.
2 code implementations • 3 Jul 2020 • Tong Qin, Tongqing Chen, Yilun Chen, Qing Su
In this paper, we exploit robust semantic features to build the map and localize vehicles in parking lots.
1 code implementation • CVPR 2020 • Yilun Chen, Shu Liu, Xiaoyong Shen, Jiaya Jia
Most state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods.
no code implementations • ICCV 2019 • Yilun Chen, Shu Liu, Xiaoyong Shen, Jiaya Jia
We present a unified, efficient and effective framework for point-cloud based 3D object detection.
no code implementations • 19 Dec 2018 • Yilun Chen, Praveen Palanisamy, Priyantha Mudalige, Katharina Muelling, John M. Dolan
In this paper, we leverage auxiliary information aside from raw images and design a novel network structure, called Auxiliary Task Network (ATN), to help boost the driving performance while maintaining the advantage of minimal training data and an End-to-End training method.
5 code implementations • CVPR 2018 • Yilun Chen, Zhicheng Wang, Yuxiang Peng, Zhiqiang Zhang, Gang Yu, Jian Sun
In this paper, we present a novel network structure called Cascaded Pyramid Network (CPN) which targets to relieve the problem from these "hard" keypoints.
Ranked #4 on Keypoint Detection on COCO test-challenge
no code implementations • 30 Apr 2013 • Kevin S. Xu, Mark Kliger, Yilun Chen, Peter J. Woolf, Alfred O. Hero III
To date, most studies on spam have focused only on the spamming phase of the spam cycle and have ignored the harvesting phase, which consists of the mass acquisition of email addresses.