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20192024
most citedInformative Dropout for Robust Representation Learning: A Shape-bias Perspective

45 citations · 66 across the 5 of their papers we have counts for

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9 papers · 1 filter

cs.CV2024

StableAnimator: High-Quality Identity-Preserving Human Image Animation

Shuyuan Tu, Zhen Xing, Xintong Han +4

Current diffusion models for human image animation struggle to ensure identity (ID) consistency. This paper presents StableAnimator, the first end-to-end ID-preserving video diffus…

cs.CV202212 cited

HiViT: Hierarchical Vision Transformer Meets Masked Image Modeling

Xiaosong Zhang, Yunjie Tian, Wei Huang +4

Recently, masked image modeling (MIM) has offered a new methodology of self-supervised pre-training of vision transformers. A key idea of efficient implementation is to discard the…

cs.CV20215 cited

Cross-Modal Attention Consistency for Video-Audio Unsupervised Learning

Shaobo Min, Qi Dai, Hongtao Xie +3

Cross-modal correlation provides an inherent supervision for video unsupervised representation learning. Existing methods focus on distinguishing different video clips by visual an…

cs.CV2021

Self-Supervised Learning with Swin Transformers

Zhenda Xie, Yutong Lin, Zhuliang Yao +4

We are witnessing a modeling shift from CNN to Transformers in computer vision. In this work, we present a self-supervised learning approach called MoBY, with Vision Transformers a…

cs.CV2020

Temporal Action Detection with Multi-level Supervision

Baifeng Shi, Qi Dai, Judy Hoffman +3

Training temporal action detection in videos requires large amounts of labeled data, yet such annotation is expensive to collect. Incorporating unlabeled or weakly-labeled data to…

cs.CV2020

Weakly-Supervised Action Localization by Generative Attention Modeling

Baifeng Shi, Qi Dai, Yadong Mu +1

Weakly-supervised temporal action localization is a problem of learning an action localization model with only video-level action labeling available. The general framework largely…