108 citations · 245 across the 9 of their papers we have counts for
9 papers
UniDA3D: A Unified Domain-Adaptive Framework for Multi-View 3D Object Detection
Hongjing Wu, Cheng Chi, Jinlin Wu +3
Camera-only 3D object detection is critical for autonomous driving, offering a cost-effective alternative to LiDAR based methods. In particular, multi-view 3D object detection has…
GarmentNets: Category-Level Pose Estimation for Garments via Canonical Space Shape Completion
Cheng Chi, Shuran Song
This paper tackles the task of category-level pose estimation for garments. With a near infinite degree of freedom, a garment's full configuration (i.e., poses) is often described…
RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
Cheng Chi, Fangyun Wei, Han Hu
Existing object detection frameworks are usually built on a single format of object/part representation, i.e., anchor/proposal rectangle boxes in RetinaNet and Faster R-CNN, center…
Loss Function Search for Face Recognition
Xiaobo Wang, Shuo Wang, Cheng Chi +2
In face recognition, designing margin-based (e.g., angular, additive, additive angular margins) softmax loss functions plays an important role in learning discriminative features.…
Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection
Shifeng Zhang, Cheng Chi, Yongqiang Yao +2
Object detection has been dominated by anchor-based detectors for several years. Recently, anchor-free detectors have become popular due to the proposal of FPN and Focal Loss. In t…
Relational Learning for Joint Head and Human Detection
Cheng Chi, Shifeng Zhang, Junliang Xing +3
Head and human detection have been rapidly improved with the development of deep convolutional neural networks. However, these two tasks are often studied separately without consid…
PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes
Cheng Chi, Shifeng Zhang, Junliang Xing +3
Pedestrian detection in crowded scenes is a challenging problem, because occlusion happens frequently among different pedestrians. In this paper, we propose an effective and effici…
RefineFace: Refinement Neural Network for High Performance Face Detection
Shifeng Zhang, Cheng Chi, Zhen Lei +1
Face detection has achieved significant progress in recent years. However, high performance face detection still remains a very challenging problem, especially when there exists ma…
UG Track 2: A Collective Benchmark Effort for Evaluating and Advancing Image Understanding in Poor Visibility Environments
Ye Yuan, Wenhan Yang, Wenqi Ren +3
The UG challenge in IEEE CVPR 2019 aims to evoke a comprehensive discussion and exploration about how low-level vision techniques can benefit the high-level automatic visual…