462 citations · 719 across the 22 of their papers we have counts for
7 papers · 1 filter
AI Oriented Large-Scale Video Management for Smart City: Technologies, Standards and Beyond
Lingyu Duan, Yihang Lou, Shiqi Wang +2
Deep learning has achieved substantial success in a series of tasks in computer vision. Intelligent video analysis, which can be broadly applied to video surveillance in various sm…
Spatial-Temporal Residue Network Based In-Loop Filter for Video Coding
Chuanmin Jia, Shiqi Wang, Xinfeng Zhang +2
Deep learning has demonstrated tremendous break through in the area of image/video processing. In this paper, a spatial-temporal residue network (STResNet) based in-loop filter is…
Image Quality Assessment Guided Deep Neural Networks Training
Zhuo Chen, Weisi Lin, Shiqi Wang +2
For many computer vision problems, the deep neural networks are trained and validated based on the assumption that the input images are pristine (i.e., artifact-free). However, dig…
Fast MPEG-CDVS Encoder with GPU-CPU Hybrid Computing
Lingyu Duan, Wei Sun, Xinfeng Zhang +7
The compact descriptors for visual search (CDVS) standard from ISO/IEC moving pictures experts group (MPEG) has succeeded in enabling the interoperability for efficient and effecti…
Compact Descriptors for Video Analysis: the Emerging MPEG Standard
Ling-Yu Duan, Vijay Chandrasekhar, Shiqi Wang +6
This paper provides an overview of the on-going compact descriptors for video analysis standard (CDVA) from the ISO/IEC moving pictures experts group (MPEG). MPEG-CDVA targets at d…
Improving Object Detection with Region Similarity Learning
Feng Gao, Yihang Lou, Yan Bai +3
Object detection aims to identify instances of semantic objects of a certain class in images or videos. The success of state-of-the-art approaches is attributed to the significant…
Incorporating Intra-Class Variance to Fine-Grained Visual Recognition
Yan Bai, Feng Gao, Yihang Lou +3
Fine-grained visual recognition aims to capture discriminative characteristics amongst visually similar categories. The state-of-the-art research work has significantly improved th…