441 citations · 803 across the 22 of their papers we have counts for
25 papers
Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs
Qi Li, Yanzhe Zhao, Yongxin Zhou +4
Multimodal Large Language Models (MLLMs) have shown immense promise in universal multimodal retrieval, which aims to find relevant items of various modalities for a given query. Ho…
Motion-Guided Masking for Spatiotemporal Representation Learning
David Fan, Jue Wang, Shuai Liao +5
Several recent works have directly extended the image masked autoencoder (MAE) with random masking into video domain, achieving promising results. However, unlike images, both spat…
Selective Structured State-Spaces for Long-Form Video Understanding
Jue Wang, Wentao Zhu, Pichao Wang +4
Effective modeling of complex spatiotemporal dependencies in long-form videos remains an open problem. The recently proposed Structured State-Space Sequence (S4) model with its lin…
Truncate-Split-Contrast: A Framework for Learning from Mislabeled Videos
Zixiao Wang, Junwu Weng, Chun Yuan +1
Learning with noisy label (LNL) is a classic problem that has been extensively studied for image tasks, but much less for video in the literature. A straightforward migration from…
LocVTP: Video-Text Pre-training for Temporal Localization
Meng Cao, Tianyu Yang, Junwu Weng +3
Video-Text Pre-training (VTP) aims to learn transferable representations for various downstream tasks from large-scale web videos. To date, almost all existing VTP methods are limi…
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition
Shoufa Chen, Chongjian Ge, Zhan Tong +4
Pretraining Vision Transformers (ViTs) has achieved great success in visual recognition. A following scenario is to adapt a ViT to various image and video recognition tasks. The ad…