8 citations · 10 across the 6 of their papers we have counts for
6 papers · 1 filter
BeatDance: Generating Beat-Consistent 3D Dance with Hierarchical Spatial-Temporal Modeling
Xiaojian Shen, Dahu Shi, Jianrong Zhang +7
Generating realistic 3D dance from music is a challenging task that requires accurate synchronization with musical rhythms while capturing the spatial complexity of human motion. A…
DETR-ViP: Detection Transformer with Robust Discriminative Visual Prompts
Bo Qian, Dahu Shi, Xing Wei
Visual prompted object detection enables interactive and flexible definition of target categories, thereby facilitating open-vocabulary detection. Since visual prompts are derived…
Better Matching, Less Forgetting: A Quality-Guided Matcher for Transformer-based Incremental Object Detection
Qirui Wu, Shizhou Zhang, De Cheng +4
Incremental Object Detection (IOD) aims to continuously learn new object classes without forgetting previously learned ones. A persistent challenge is catastrophic forgetting, prim…
Scene-Adaptive Attention Network for Crowd Counting
Xing Wei, Yuanrui Kang, Jihao Yang +4
In recent years, significant progress has been made on the research of crowd counting. However, as the challenging scale variations and complex scenes existed in crowds, neither tr…
SOIT: Segmenting Objects with Instance-Aware Transformers
Xiaodong Yu, Dahu Shi, Xing Wei +3
This paper presents an end-to-end instance segmentation framework, termed SOIT, that Segments Objects with Instance-aware Transformers. Inspired by DETR \cite{carion2020end}, our m…
InsPose: Instance-Aware Networks for Single-Stage Multi-Person Pose Estimation
Dahu Shi, Xing Wei, Xiaodong Yu +3
Multi-person pose estimation is an attractive and challenging task. Existing methods are mostly based on two-stage frameworks, which include top-down and bottom-up methods. Two-sta…