1 code implementation • 7 Apr 2024 • Yingsen Zeng, Yujie Zhong, Chengjian Feng, Lin Ma
Temporal Action Detection (TAD) focuses on detecting pre-defined actions, while Moment Retrieval (MR) aims to identify the events described by open-ended natural language within untrimmed videos.
Ranked #2 on Natural Language Moment Retrieval on ActivityNet Captions (R@5,IoU=0.5 metric)
no code implementations • 8 Feb 2024 • Chengjian Feng, Yujie Zhong, Zequn Jie, Weidi Xie, Lin Ma
The grounding head is trained to align the text embedding of category names with the regional visual feature of the diffusion model, using supervision from an off-the-shelf object detector, and a novel self-training scheme on (novel) categories not covered by the detector.
1 code implementation • 5 Feb 2023 • Sifan Zhou, Zhi Tian, Xiangxiang Chu, Xinyu Zhang, Bo Zhang, Xiaobo Lu, Chengjian Feng, Zequn Jie, Patrick Yin Chiang, Lin Ma
The deployment of 3D detectors strikes one of the major challenges in real-world self-driving scenarios.
1 code implementation • CVPR 2023 • Chengjian Feng, Zequn Jie, Yujie Zhong, Xiangxiang Chu, Lin Ma
However, the typical convolution ignores the radial symmetry of the BEV features and increases the difficulty of the detector optimization.
2 code implementations • 30 Mar 2022 • Chengjian Feng, Yujie Zhong, Zequn Jie, Xiangxiang Chu, Haibing Ren, Xiaolin Wei, Weidi Xie, Lin Ma
The goal of this work is to establish a scalable pipeline for expanding an object detector towards novel/unseen categories, using zero manual annotations.
1 code implementation • ICCV 2021 • Chengjian Feng, Yujie Zhong, Weilin Huang
Specifically, EBL increases the intensity of the adjustment of the decision boundary for the weak classes by a designed score-guided loss margin between any two classes.
Ranked #10 on Object Detection on LVIS v1.0 val
5 code implementations • ICCV 2021 • Chengjian Feng, Yujie Zhong, Yu Gao, Matthew R. Scott, Weilin Huang
One-stage object detection is commonly implemented by optimizing two sub-tasks: object classification and localization, using heads with two parallel branches, which might lead to a certain level of spatial misalignment in predictions between the two tasks.
Ranked #3 on 2D Object Detection on CeyMo
no code implementations • 10 Oct 2018 • Jiawei Wang, Zhaoshui He, Chengjian Feng, Zhouping Zhu, Qinzhuang Lin, Jun Lv, Shengli Xie
Data collection and annotation are time-consuming in machine learning, expecially for large scale problem.