71 citations · 225 across the 30 of their papers we have counts for
7 papers · 1 filter
Deep Self-Paced Learning for Person Re-Identification
Sanping Zhou, Jinjun Wang, Deyu Meng +4
Person re-identification (Re-ID) usually suffers from noisy samples with background clutter and mutual occlusion, which makes it extremely difficult to distinguish different indivi…
Large Margin Learning in Set to Set Similarity Comparison for Person Re-identification
Sanping Zhou, Jinjun Wang, Rui Shi +3
Person re-identification (Re-ID) aims at matching images of the same person across disjoint camera views, which is a challenging problem in multimedia analysis, multimedia editing…
Deep Feature Learning via Structured Graph Laplacian Embedding for Person Re-Identification
De Cheng, Yihong Gong, Zhihui Li +3
Learning the distance metric between pairs of examples is of great importance for visual recognition, especially for person re-identification (Re-Id). Recently, the contrastive and…
Detecting Drivable Area for Self-driving Cars: An Unsupervised Approach
Ziyi Liu, Siyu Yu, Xiao Wang +1
It has been well recognized that detecting drivable area is central to self-driving cars. Most of existing methods attempt to locate road surface by using lane line, thereby restri…
Single Image Super Resolution - When Model Adaptation Matters
Yudong Liang, Radu Timofte, Jinjun Wang +2
In the recent years impressive advances were made for single image super-resolution. Deep learning is behind a big part of this success. Deep(er) architecture design and external p…
Single Image Super-resolution via a Lightweight Residual Convolutional Neural Network
Yudong Liang, Ze Yang, Kai Zhang +3
Recent years have witnessed great success of convolutional neural network (CNN) for various problems both in low and high level visions. Especially noteworthy is the residual netwo…
Brain Inspired Cognitive Model with Attention for Self-Driving Cars
Shitao Chen, Songyi Zhang, Jinghao Shang +2
Perception-driven approach and end-to-end system are two major vision-based frameworks for self-driving cars. However, it is difficult to introduce attention and historical informa…