24 citations · 44 across the 8 of their papers we have counts for
8 papers
Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer
Guangyi Chen, Xiao Liu, Guangrun Wang +4
Video-language pre-trained models have shown remarkable success in guiding video question-answering (VideoQA) tasks. However, due to the length of video sequences, training large-s…
Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment
Sheng Zhang, Muzammal Naseer, Guangyi Chen +4
Large-scale pre-trained Vision Language Models (VLMs) have proven effective for zero-shot classification. Despite the success, most traditional VLMs-based methods are restricted by…
Language-free Compositional Action Generation via Decoupling Refinement
Xiao Liu, Guangyi Chen, Yansong Tang +3
Composing simple elements into complex concepts is crucial yet challenging, especially for 3D action generation. Existing methods largely rely on extensive neural language annotati…
Adversarial Alignment for Source Free Object Detection
Qiaosong Chu, Shuyan Li, Guangyi Chen +2
Source-free object detection (SFOD) aims to transfer a detector pre-trained on a label-rich source domain to an unlabeled target domain without seeing source data. While most exist…
PromptCAL: Contrastive Affinity Learning via Auxiliary Prompts for Generalized Novel Category Discovery
Sheng Zhang, Salman Khan, Zhiqiang Shen +3
Although existing semi-supervised learning models achieve remarkable success in learning with unannotated in-distribution data, they mostly fail to learn on unlabeled data sampled…
Temporally Disentangled Representation Learning
Weiran Yao, Guangyi Chen, Kun Zhang
Recently in the field of unsupervised representation learning, strong identifiability results for disentanglement of causally-related latent variables have been established by expl…
PLOT: Prompt Learning with Optimal Transport for Vision-Language Models
Guangyi Chen, Weiran Yao, Xiangchen Song +3
With the increasing attention to large vision-language models such as CLIP, there has been a significant amount of effort dedicated to building efficient prompts. Unlike convention…
FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment
Jinglin Xu, Yongming Rao, Xumin Yu +3
Most existing action quality assessment methods rely on the deep features of an entire video to predict the score, which is less reliable due to the non-transparent inference proce…