78 citations · 413 across the 61 of their papers we have counts for
12 papers · 1 filter
Feature Calibration Network for Occluded Pedestrian Detection
Tianliang Zhang, Qixiang Ye, Baochang Zhang +3
Pedestrian detection in the wild remains a challenging problem especially for scenes containing serious occlusion. In this paper, we propose a novel feature learning method in the…
CircleNet: Reciprocating Feature Adaptation for Robust Pedestrian Detection
Tianliang Zhang, Zhenjun Han, Huijuan Xu +2
Pedestrian detection in the wild remains a challenging problem especially when the scene contains significant occlusion and/or low resolution of the pedestrians to be detected. Exi…
Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning
Xiaoyue Duan, Guoliang Kang, Runqi Wang +4
Robust Model-Agnostic Meta-Learning (MAML) is usually adopted to train a meta-model which may fast adapt to novel classes with only a few exemplars and meanwhile remain robust to a…
Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer
Yanjing Li, Sheng Xu, Baochang Zhang +3
The large pre-trained vision transformers (ViTs) have demonstrated remarkable performance on various visual tasks, but suffer from expensive computational and memory cost problems…
IDa-Det: An Information Discrepancy-aware Distillation for 1-bit Detectors
Sheng Xu, Yanjing Li, Bohan Zeng +5
Knowledge distillation (KD) has been proven to be useful for training compact object detection models. However, we observe that KD is often effective when the teacher model and stu…
FNeVR: Neural Volume Rendering for Face Animation
Bohan Zeng, Boyu Liu, Hong Li +5
Face animation, one of the hottest topics in computer vision, has achieved a promising performance with the help of generative models. However, it remains a critical challenge to g…