9 citations · 20 across the 9 of their papers we have counts for
10 papers
SportsGrounder: Proposal-Aided Interleaved Grounding for Dense Sports Video Reasoning
Yizhi Li, Jiawei Jiang, Guanhong Wang +2
Sports video analysis is crucial for athletic analytics and broadcasting enhancement. Dense sports video reasoning, however, demands a fine-grained understanding of numerous small-…
Solving the Catastrophic Forgetting Problem in Generalized Category Discovery
Xinzi Cao, Xiawu Zheng, Guanhong Wang +5
Generalized Category Discovery (GCD) aims to identify a mix of known and novel categories within unlabeled data sets, providing a more realistic setting for image recognition. Esse…
Sam-Guided Enhanced Fine-Grained Encoding with Mixed Semantic Learning for Medical Image Captioning
Zhenyu Zhang, Benlu Wang, Weijie Liang +5
With the development of multimodality and large language models, the deep learning-based technique for medical image captioning holds the potential to offer valuable diagnostic rec…
User-Aware Prefix-Tuning is a Good Learner for Personalized Image Captioning
Xuan Wang, Guanhong Wang, Wenhao Chai +2
Image captioning bridges the gap between vision and language by automatically generating natural language descriptions for images. Traditional image captioning methods often overlo…
FrameRS: A Video Frame Compression Model Composed by Self supervised Video Frame Reconstructor and Key Frame Selector
Qiqian Fu, Guanhong Wang, Gaoang Wang
In this paper, we present frame reconstruction model: FrameRS. It consists self-supervised video frame reconstructor and key frame selector. The frame reconstructor, FrameMAE, is d…
A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision
Zhonghan Zhao, Wenhao Chai, Shengyu Hao +6
Deep learning has the potential to revolutionize sports performance, with applications ranging from perception and comprehension to decision. This paper presents a comprehensive su…
MovieChat: From Dense Token to Sparse Memory for Long Video Understanding
Enxin Song, Wenhao Chai, Guanhong Wang +10
Recently, integrating video foundation models and large language models to build a video understanding system can overcome the limitations of specific pre-defined vision tasks. Yet…
Missing Modality meets Meta Sampling (M3S): An Efficient Universal Approach for Multimodal Sentiment Analysis with Missing Modality
Haozhe Chi, Minghua Yang, Junhao Zhu +2
Multimodal sentiment analysis (MSA) is an important way of observing mental activities with the help of data captured from multiple modalities. However, due to the recording or tra…
Preserve Pre-trained Knowledge: Transfer Learning With Self-Distillation For Action Recognition
Yang Zhou, Zhanhao He, Keyu Lu +2
Video-based action recognition is one of the most popular topics in computer vision. With recent advances of selfsupervised video representation learning approaches, action recogni…
Human-Centered Prior-Guided and Task-Dependent Multi-Task Representation Learning for Action Recognition Pre-Training
Guanhong Wang, Keyu Lu, Yang Zhou +2
Recently, much progress has been made for self-supervised action recognition. Most existing approaches emphasize the contrastive relations among videos, including appearance and mo…