activity
20142023
most citedResidual Attention Network for Image Classification

313 citations · 1k across the 44 of their papers we have counts for

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Showing 2020Show all

14 papers · 1 filter

cs.CV2020★ 16 cited

AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection

Hao Zhu, Chaoyou Fu, Qianyi Wu +3

Recent studies have shown that the performance of forgery detection can be improved with diverse and challenging Deepfakes datasets. However, due to the lack of Deepfakes datasets…

cs.CV2020★ 3 cited

Data Agnostic Filter Gating for Efficient Deep Networks

Xiu Su, Shan You, Tao Huang +5

To deploy a well-trained CNN model on low-end computation edge devices, it is usually supposed to compress or prune the model under certain computation budget (e.g., FLOPs). Curren…

cs.CV2020★ 36 cited

ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding

Yibo Yang, Hongyang Li, Shan You +3

Neural architecture search (NAS) aims to produce the optimal sparse solution from a high-dimensional space spanned by all candidate connections. Current gradient-based NAS methods…

cs.CV2020★ 7 cited

HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation

Jiefeng Li, Can Wang, Wentao Liu +2

Remarkable progress has been made in 3D human pose estimation from a monocular RGB camera. However, only a few studies explored 3D multi-person cases. In this paper, we attempt to…

cs.CV2020★ 15 cited

Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimation

Sheng Jin, Wentao Liu, Enze Xie +4

Multi-person pose estimation is challenging because it localizes body keypoints for multiple persons simultaneously. Previous methods can be divided into two streams, i.e. top-down…

cs.CV2020★ 4 cited

Whole-Body Human Pose Estimation in the Wild

Sheng Jin, Lumin Xu, Jin Xu +5

This paper investigates the task of 2D human whole-body pose estimation, which aims to localize dense landmarks on the entire human body including face, hands, body, and feet. As e…