1 code implementation • 13 Mar 2024 • Bowen Li, Wenhan Wu, Ziwei Tang, Lin Shi, John Yang, Jinyang Li, Shunyu Yao, Chen Qian, Binyuan Hui, Qicheng Zhang, Zhiyin Yu, He Du, Ping Yang, Dahua Lin, Chao Peng, Kai Chen
Recent advancements in large language models (LLMs) have significantly enhanced their coding capabilities.
no code implementations • 4 Sep 2023 • Chao Peng, Zhengwei Lv, Jiarong Fu, Jiayuan Liang, Zhao Zhang, Ajitha Rajan, Ping Yang
We find that Hawkeye is able to generate GUI event sequences targeting changed functions more reliably than FastBot2 and ARES for the open source Apps and the large commercial App.
1 code implementation • 19 Jul 2023 • Guohai Xu, Jiayi Liu, Ming Yan, Haotian Xu, Jinghui Si, Zhuoran Zhou, Peng Yi, Xing Gao, Jitao Sang, Rong Zhang, Ji Zhang, Chao Peng, Fei Huang, Jingren Zhou
In this paper, we present CValues, the first Chinese human values evaluation benchmark to measure the alignment ability of LLMs in terms of both safety and responsibility criteria.
no code implementations • 17 Dec 2020 • Andrei Afanasev, Jaseer Ahmed, Igor Akushevich, Jan C. Bernauer, Peter G. Blunden, Andrea Bressan, Duane Byer, Ethan Cline, Markus Diefenthaler, Jan M. Friedrich, Haiyan Gao, Alexandr Ilyichev, Ulrich D. Jentschura, Vladimir Khachatryan, Lin Li, Wally Melnitchouk, Richard Milner, Fred Myhrer, Chao Peng, Jianwei Qiu, Udit Raha, Axel Schmidt, Vanamali C. Shastry, Hubert Spiesberger, Stan Srednyak, Steffen Strauch, Pulak Talukdar, Weizhi Xiong
Current precision scattering experiments and even more so many experiments planed for the Electron Ion Collider will be limited by systematics.
Nuclear Theory
2 code implementations • MIDL 2019 • Jun Ma, Zhan Wei, Yiwen Zhang, Yixin Wang, Rongfei Lv, Cheng Zhu, Gaoxiang Chen, Jianan Liu, Chao Peng, Lei Wang, Yunpeng Wang, Jianan Chen
The \emph{second contribution} is that we systematically evaluated five benchmark methods on two representative public datasets.
no code implementations • CVPR 2019 • Huanyu Liu, Chao Peng, Changqian Yu, Jingbo Wang, Xu Liu, Gang Yu, Wei Jiang
Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic.
no code implementations • ECCV 2018 • Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun
(1) Recent object detectors like FPN and RetinaNet usually involve extra stages against the task of image classification to handle the objects with various scales.
18 code implementations • ECCV 2018 • Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang
Semantic segmentation requires both rich spatial information and sizeable receptive field.
Ranked #4 on Semantic Segmentation on SkyScapes-Dense
Dichotomous Image Segmentation Real-Time Semantic Segmentation +2
3 code implementations • CVPR 2018 • Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang
Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction.
Ranked #5 on Semantic Segmentation on PASCAL VOC 2012 test
2 code implementations • 17 Apr 2018 • Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun
Due to the gap between the image classification and object detection, we propose DetNet in this paper, which is a novel backbone network specifically designed for object detection.
no code implementations • ECCV 2018 • Zhenli Zhang, Xiangyu Zhang, Chao Peng, Dazhi Cheng, Jian Sun
Modern semantic segmentation frameworks usually combine low-level and high-level features from pre-trained backbone convolutional models to boost performance.
Ranked #4 on Semantic Segmentation on PASCAL VOC 2012 val (using extra training data)
6 code implementations • CVPR 2018 • Chao Peng, Tete Xiao, Zeming Li, Yuning Jiang, Xiangyu Zhang, Kai Jia, Gang Yu, Jian Sun
The improvements in recent CNN-based object detection works, from R-CNN [11], Fast/Faster R-CNN [10, 31] to recent Mask R-CNN [14] and RetinaNet [24], mainly come from new network, new framework, or novel loss design.
5 code implementations • 20 Nov 2017 • Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun
More importantly, simply replacing the backbone with a tiny network (e. g, Xception), our Light-Head R-CNN gets 30. 7 mmAP at 102 FPS on COCO, significantly outperforming the single-stage, fast detectors like YOLO and SSD on both speed and accuracy.
2 code implementations • CVPR 2017 • Chao Peng, Xiangyu Zhang, Gang Yu, Guiming Luo, Jian Sun
One of recent trends [30, 31, 14] in network architec- ture design is stacking small filters (e. g., 1x1 or 3x3) in the entire network because the stacked small filters is more ef- ficient than a large kernel, given the same computational complexity.
Ranked #8 on Semantic Segmentation on PASCAL VOC 2012 val