activity
20142024
most citedTemporal Segment Networks: Towards Good Practices for Deep Action Recognition

289 citations · 636 across the 34 of their papers we have counts for

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32 papers · 1 filter

cs.CV20241 cited

Efficient Test-Time Prompt Tuning for Vision-Language Models

Yuhan Zhu, Guozhen Zhang, Chen Xu +4

Vision-language models have showcased impressive zero-shot classification capabilities when equipped with suitable text prompts. Previous studies have shown the effectiveness of te…

cs.CV20241 cited

OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text

Qingyun Li, Zhe Chen, Weiyun Wang +37

Image-text interleaved data, consisting of multiple images and texts arranged in a natural document format, aligns with the presentation paradigm of internet data and closely resem…

cs.CV2024

VideoEval: Comprehensive Benchmark Suite for Low-Cost Evaluation of Video Foundation Model

Xinhao Li, Zhenpeng Huang, Jing Wang +2

With the growth of high-quality data and advancement in visual pre-training paradigms, Video Foundation Models (VFMs) have made significant progress recently, demonstrating their r…

cs.CV20242 cited

AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation

Yuhan Zhu, Yuyang Ji, Zhiyu Zhao +2

Pre-trained vision-language models (VLMs) have shown impressive results in various visual classification tasks. However, we often fail to fully unleash their potential when adaptin…

cs.CV2024

STMixer: A One-Stage Sparse Action Detector

Tao Wu, Mengqi Cao, Ziteng Gao +2

Traditional video action detectors typically adopt the two-stage pipeline, where a person detector is first employed to generate actor boxes and then 3D RoIAlign is used to extract…

cs.CV2024

SportsHHI: A Dataset for Human-Human Interaction Detection in Sports Videos

Tao Wu, Runyu He, Gangshan Wu +1

Video-based visual relation detection tasks, such as video scene graph generation, play important roles in fine-grained video understanding. However, current video visual relation…