216 citations · 1.9k across the 97 of their papers we have counts for
11 papers · 1 filter
Quantization Networks
Jiwei Yang, Xu Shen, Jun Xing +5
Although deep neural networks are highly effective, their high computational and memory costs severely challenge their applications on portable devices. As a consequence, low-bit q…
Video-based compression for plenoptic point clouds
Li Li, Zhu Li, Shan Liu +1
The plenoptic point cloud that has multiple colors from various directions, is a more complete representation than the general point cloud that usually has only one color. It is mo…
Progressive Unsupervised Person Re-identification by Tracklet Association with Spatio-Temporal Regularization
Qiaokang Xie, Wengang Zhou, Guo-Jun Qi +2
Existing methods for person re-identification (Re-ID) are mostly based on supervised learning which requires numerous manually labeled samples across all camera views for training.…
An End-to-End Foreground-Aware Network for Person Re-Identification
Yiheng Liu, Wengang Zhou, Jianzhuang Liu +3
Person re-identification is a crucial task of identifying pedestrians of interest across multiple surveillance camera views. In person re-identification, a pedestrian is usually re…
Relation Distillation Networks for Video Object Detection
Jiajun Deng, Yingwei Pan, Ting Yao +3
It has been well recognized that modeling object-to-object relations would be helpful for object detection. Nevertheless, the problem is not trivial especially when exploring the i…
Real-Time Correlation Tracking via Joint Model Compression and Transfer
Ning Wang, Wengang Zhou, Yibing Song +2
Correlation filters (CF) have received considerable attention in visual tracking because of their computational efficiency. Leveraging deep features via off-the-shelf CNN models (e…
Online Filter Clustering and Pruning for Efficient Convnets
Zhengguang Zhou, Wengang Zhou, Richang Hong +1
Pruning filters is an effective method for accelerating deep neural networks (DNNs), but most existing approaches prune filters on a pre-trained network directly which limits in ac…
Progressive Learning of Low-Precision Networks
Zhengguang Zhou, Wengang Zhou, Xutao Lv +3
Recent years have witnessed the great advance of deep learning in a variety of vision tasks. Many state-of-the-art deep neural networks suffer from large size and high complexity,…
Deep Learning-Based Video Coding: A Review and A Case Study
Dong Liu, Yue Li, Jianping Lin +2
The past decade has witnessed great success of deep learning technology in many disciplines, especially in computer vision and image processing. However, deep learning-based video…
Unsupervised Deep Tracking
Ning Wang, Yibing Song, Chao Ma +3
We propose an unsupervised visual tracking method in this paper. Different from existing approaches using extensive annotated data for supervised learning, our CNN model is trained…
Occupancy-map-based rate distortion optimization for video-based point cloud compression
Li Li, Zhu Li, Shan Liu +1
The state-of-the-art video-based point cloud compression scheme projects the 3D point cloud to 2D patch by patch and organizes the patches into frames to compress them using the ef…