activity
20142022
most citedVideo Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics

262 citations · 1.9k across the 68 of their papers we have counts for

collaborators
Showing 2014Show all

6 papers · 1 filter

cs.CV2014

Robust Estimation of 3D Human Poses from a Single Image

Chunyu Wang, Yizhou Wang, Zhouchen Lin +2

Human pose estimation is a key step to action recognition. We propose a method of estimating 3D human poses from a single image, which works in conjunction with an existing 2D pose…

cs.LG2014★ 1 cited

Exploring Algorithmic Limits of Matrix Rank Minimization under Affine Constraints

Bo Xin, David Wipf

Many applications require recovering a matrix of minimal rank within an affine constraint set, with matrix completion a notable special case. Because the problem is NP-hard in gene…

cs.CV2014

Group-based Sparse Representation for Image Restoration

Jian Zhang, Debin Zhao, Wen Gao

Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high compu…

cs.MM2014★ 189 cited

Image Restoration Using Joint Statistical Modeling in Space-Transform Domain

Jian Zhang, Debin Zhao, Ruiqin Xiong +2

This paper presents a novel strategy for high-fidelity image restoration by characterizing both local smoothness and nonlocal self-similarity of natural images in a unified statist…

cs.CV2014★ 183 cited

Image Compressive Sensing Recovery Using Adaptively Learned Sparsifying Basis via L0 Minimization

Jian Zhang, Chen Zhao, Debin Zhao +1

From many fewer acquired measurements than suggested by the Nyquist sampling theory, compressive sensing (CS) theory demonstrates that, a signal can be reconstructed with high prob…

cs.CV2014

Structural Group Sparse Representation for Image Compressive Sensing Recovery

Jian Zhang, Debin Zhao, Feng Jiang +1

Compressive Sensing (CS) theory shows that a signal can be decoded from many fewer measurements than suggested by the Nyquist sampling theory, when the signal is sparse in some dom…