activity
20172024
most citedSemantic Graph Convolutional Networks for 3D Human Pose Regression

521 citations · 786 across the 34 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV2021

COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality

Honglu Zhou, Asim Kadav, Aviv Shamsian +6

Group Activity Recognition detects the activity collectively performed by a group of actors, which requires compositional reasoning of actors and objects. We approach the task by m…

cs.CV2021★ 5 cited

Out-of-Domain Generalization from a Single Source: An Uncertainty Quantification Approach

Xi Peng, Fengchun Qiao, Long Zhao

We are concerned with a worst-case scenario in model generalization, in the sense that a model aims to perform well on many unseen domains while there is only one single domain ava…

cs.CV2021★ 3 cited

Improved Transformer for High-Resolution GANs

Long Zhao, Zizhao Zhang, Ting Chen +2

Attention-based models, exemplified by the Transformer, can effectively model long range dependency, but suffer from the quadratic complexity of self-attention operation, making th…

cs.CV2021★ 4 cited

Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding

Zizhao Zhang, Han Zhang, Long Zhao +3

Hierarchical structures are popular in recent vision transformers, however, they require sophisticated designs and massive datasets to work well. In this paper, we explore the idea…

cs.CV2021★ 1 cited

More Than Just Attention: Improving Cross-Modal Attentions with Contrastive Constraints for Image-Text Matching

Yuxiao Chen, Jianbo Yuan, Long Zhao +4

Cross-modal attention mechanisms have been widely applied to the image-text matching task and have achieved remarkable improvements thanks to its capability of learning fine-graine…

cs.CV2021★ 12 cited

SMIL: Multimodal Learning with Severely Missing Modality

Mengmeng Ma, Jian Ren, Long Zhao +3

A common assumption in multimodal learning is the completeness of training data, i.e., full modalities are available in all training examples. Although there exists research endeav…