32 citations · 60 across the 10 of their papers we have counts for
10 papers
SafeLoop: Risk-Aware Rollback for Vision-Language-Action Manipulation
Zeyu Lou, Tianran Zhang, Xinquan Yue +2
Recent vision-language-action (VLA) models are promising for general-purpose manipulation, but long-horizon execution remains fragile. Small state-estimation or control errors can…
PL-NBA: A Possession-level Universal Basketball Video Dataset Supporting Multiple Visual Understanding Tasks
Yunhao Zhao, Haoying Sun, Jiarui Li +5
Visual understanding in sports has emerged as a hot topic in computer vision in recent years. Most existing basketball video datasets adopt single action or activity as sample, whi…
NBA_Streaming: A Large-Scale Benchmark for Fine-Grained Basketball Commentary Generation in Continuous Streams
Lifang Wu, Yuyang Wu, Yangdong Gao +3
Live basketball commentary generation requires determining when an event is sufficiently observable and describing it before subsequent events unfold. However, existing methods are…
Watching Synthetic Videos: Aligning Cross-modal Representations with Visual Synthesis for Zero-shot Video Captioning
Liangyu Fu, Junbo Wang, Yuke Li +3
Text-only training is a popular paradigm in zero-shot video captioning, where the video distribution is not available to the model during training, leading to a cross-modal gap bet…
Exploring Visual Pre-training for Robot Manipulation: Datasets, Models and Methods
Ya Jing, Xuelin Zhu, Xingbin Liu +4
Visual pre-training with large-scale real-world data has made great progress in recent years, showing great potential in robot learning with pixel observations. However, the recipe…
Learning to Explore Informative Trajectories and Samples for Embodied Perception
Ya Jing, Tao Kong
We are witnessing significant progress on perception models, specifically those trained on large-scale internet images. However, efficiently generalizing these perception models to…
Towards Unifying Reference Expression Generation and Comprehension
Duo Zheng, Tao Kong, Ya Jing +2
Reference Expression Generation (REG) and Comprehension (REC) are two highly correlated tasks. Modeling REG and REC simultaneously for utilizing the relation between them is a prom…
Locate then Segment: A Strong Pipeline for Referring Image Segmentation
Ya Jing, Tao Kong, Wei Wang +3
Referring image segmentation aims to segment the objects referred by a natural language expression. Previous methods usually focus on designing an implicit and recurrent feature in…
Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search
Ya Jing, Chenyang Si, Junbo Wang +3
Text-based person search aims to retrieve the corresponding person images in an image database by virtue of a describing sentence about the person, which poses great potential for…
Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning
Chenyang Si, Ya Jing, Wei Wang +2
Skeleton-based action recognition has made great progress recently, but many problems still remain unsolved. For example, most of the previous methods model the representations of…