activity
20162026
most citedHuman Action Forecasting by Learning Task Grammars

12 citations · 26 across the 7 of their papers we have counts for

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14 papers · 1 filter

cs.CV2026

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…

cs.CV2023

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…

cs.CV20233 cited

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…

cs.CV20225 cited

Unsupervised Pre-training for Temporal Action Localization Tasks

Can Zhang, Tianyu Yang, Junwu Weng +3

Unsupervised video representation learning has made remarkable achievements in recent years. However, most existing methods are designed and optimized for video classification. The…

cs.CV20216 cited

Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning

Chongjian Ge, Youwei Liang, Yibing Song +3

Studies on self-supervised visual representation learning (SSL) improve encoder backbones to discriminate training samples without labels. While CNN encoders via SSL achieve compar…

cs.CV2021

Generalized One-Class Learning Using Pairs of Complementary Classifiers

Anoop Cherian, Jue Wang

One-class learning is the classic problem of fitting a model to the data for which annotations are available only for a single class. In this paper, we explore novel objectives for…