16 citations · 130 across the 33 of their papers we have counts for
6 papers · 1 filter
Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer Learning
Huanjin Yao, Wenhao Wu, Zhiheng Li
Large pre-trained vision models achieve impressive success in computer vision. However, fully fine-tuning large models for downstream tasks, particularly in video understanding, ca…
GPT4Vis: What Can GPT-4 Do for Zero-shot Visual Recognition?
Wenhao Wu, Huanjin Yao, Mengxi Zhang +3
This paper does not present a novel method. Instead, it delves into an essential, yet must-know baseline in light of the latest advancements in Generative Artificial Intelligence (…
What Can Simple Arithmetic Operations Do for Temporal Modeling?
Wenhao Wu, Yuxin Song, Zhun Sun +3
Temporal modeling plays a crucial role in understanding video content. To tackle this problem, previous studies built complicated temporal relations through time sequence thanks to…
UATVR: Uncertainty-Adaptive Text-Video Retrieval
Bo Fang, Wenhao Wu, Chang Liu +6
With the explosive growth of web videos and emerging large-scale vision-language pre-training models, e.g., CLIP, retrieving videos of interest with text instructions has attracted…
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?
Wenhao Wu, Haipeng Luo, Bo Fang +2
Most existing text-video retrieval methods focus on cross-modal matching between the visual content of videos and textual query sentences. However, in real-world scenarios, online…
Bidirectional Cross-Modal Knowledge Exploration for Video Recognition with Pre-trained Vision-Language Models
Wenhao Wu, Xiaohan Wang, Haipeng Luo +3
Vision-language models (VLMs) pre-trained on large-scale image-text pairs have demonstrated impressive transferability on various visual tasks. Transferring knowledge from such pow…