5 papers · 1 filter
NADER: Neural Architecture Design via Multi-Agent Collaboration
Zekang Yang, Wang Zeng, Sheng Jin +3
Designing effective neural architectures poses a significant challenge in deep learning. While Neural Architecture Search (NAS) automates the search for optimal architectures, exis…
UniFS: Universal Few-shot Instance Perception with Point Representations
Sheng Jin, Ruijie Yao, Lumin Xu +4
Instance perception tasks (object detection, instance segmentation, pose estimation, counting) play a key role in industrial applications of visual models. As supervised learning m…
TCFormer: Visual Recognition via Token Clustering Transformer
Wang Zeng, Sheng Jin, Lumin Xu +5
Transformers are widely used in computer vision areas and have achieved remarkable success. Most state-of-the-art approaches split images into regular grids and represent each grid…
When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark Dataset
Yi Zhang, Wang Zeng, Sheng Jin +3
Recent years have witnessed increasing research attention towards pedestrian detection by taking the advantages of different sensor modalities (e.g. RGB, IR, Depth, LiDAR and Event…
You Only Learn One Query: Learning Unified Human Query for Single-Stage Multi-Person Multi-Task Human-Centric Perception
Sheng Jin, Shuhuai Li, Tong Li +3
Human-centric perception (e.g. detection, segmentation, pose estimation, and attribute analysis) is a long-standing problem for computer vision. This paper introduces a unified and…