24 citations · 97 across the 24 of their papers we have counts for
26 papers
STORM: End-to-End Referring Multi-Object Tracking in Videos
Zijia Lu, Jingru Yi, Jue Wang +4
Referring multi-object tracking (RMOT) is a task of associating all the objects in a video that semantically match with given textual queries or referring expressions. Existing RMO…
Early Action Recognition with Action Prototypes
Guglielmo Camporese, Alessandro Bergamo, Xunyu Lin +2
Early action recognition is an important and challenging problem that enables the recognition of an action from a partially observed video stream where the activity is potentially…
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild
Haodong Duan, Mingze Xu, Bing Shuai +4
We present SkeleTR, a new framework for skeleton-based action recognition. In contrast to prior work, which focuses mainly on controlled environments, we target more general scenar…
ScaleDet: A Scalable Multi-Dataset Object Detector
Yanbei Chen, Manchen Wang, Abhay Mittal +4
Multi-dataset training provides a viable solution for exploiting heterogeneous large-scale datasets without extra annotation cost. In this work, we propose a scalable multi-dataset…
Benchmarking Zero-Shot Recognition with Vision-Language Models: Challenges on Granularity and Specificity
Zhenlin Xu, Yi Zhu, Tiffany Deng +6
This paper presents novel benchmarks for evaluating vision-language models (VLMs) in zero-shot recognition, focusing on granularity and specificity. Although VLMs excel in tasks li…
Musketeer: Joint Training for Multi-task Vision Language Model with Task Explanation Prompts
Zhaoyang Zhang, Yantao Shen, Kunyu Shi +7
We present a vision-language model whose parameters are jointly trained on all tasks and fully shared among multiple heterogeneous tasks which may interfere with each other, result…