most citedAugmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic Segmentation

8 citations · 19 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20228 cited

Augmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic Segmentation

Zhen Zhao, Lihe Yang, Sifan Long +3

Recent studies on semi-supervised semantic segmentation (SSS) have seen fast progress. Despite their promising performance, current state-of-the-art methods tend to increasingly co…

cs.CV20223 cited

Instance-specific and Model-adaptive Supervision for Semi-supervised Semantic Segmentation

Zhen Zhao, Sifan Long, Jimin Pi +2

Recently, semi-supervised semantic segmentation has achieved promising performance with a small fraction of labeled data. However, most existing studies treat all unlabeled data eq…

cs.CV2022

Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision Transformers

Sifan Long, Zhen Zhao, Jimin Pi +2

Vision transformers have achieved significant improvements on various vision tasks but their quadratic interactions between tokens significantly reduce computational efficiency. Ma…

cs.CV20228 cited

CAE v2: Context Autoencoder with CLIP Target

Xinyu Zhang, Jiahui Chen, Junkun Yuan +10

Masked image modeling (MIM) learns visual representation by masking and reconstructing image patches. Applying the reconstruction supervision on the CLIP representation has been pr…

eess.IV2018

Multimodal Utterance-level Affect Analysis using Visual, Audio and Text Features

Didan Deng, Yuqian Zhou, Jimin Pi +1

The integration of information across multiple modalities and across time is a promising way to enhance the emotion recognition performance of affective systems. Much previous work…