1.8k citations · 3k across the 32 of their papers we have counts for
32 papers
Switchable Representation Learning Framework with Self-compatibility
Shengsen Wu, Yan Bai, Yihang Lou +3
Real-world visual search systems involve deployments on multiple platforms with different computing and storage resources. Deploying a unified model that suits the minimal-constrai…
Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate Domains
Yongxing Dai, Yifan Sun, Jun Liu +3
Cross-domain person re-identification (re-ID), such as unsupervised domain adaptive (UDA) re-ID, aims to transfer the identity-discriminative knowledge from the source to the targe…
mc-BEiT: Multi-choice Discretization for Image BERT Pre-training
Xiaotong Li, Yixiao Ge, Kun Yi +3
Image BERT pre-training with masked image modeling (MIM) becomes a popular practice to cope with self-supervised representation learning. A seminal work, BEiT, casts MIM as a class…
Towards Low Light Enhancement with RAW Images
Haofeng Huang, Wenhan Yang, Yueyu Hu +2
In this paper, we make the first benchmark effort to elaborate on the superiority of using RAW images in the low light enhancement and develop a novel alternative route to utilize…
Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analytics
Wenhan Yang, Haofeng Huang, Yueyu Hu +2
Video Coding for Machines (VCM) is committed to bridging to an extent separate research tracks of video/image compression and feature compression, and attempts to optimize compactn…
Dual-Tuning: Joint Prototype Transfer and Structure Regularization for Compatible Feature Learning
Yan Bai, Jile Jiao, Shengsen Wu +4
Visual retrieval system faces frequent model update and deployment. It is a heavy workload to re-extract features of the whole database every time.Feature compatibility enables the…
IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID
Yongxing Dai, Jun Liu, Yifan Sun +3
Unsupervised domain adaptive person re-identification (UDA re-ID) aims at transferring the labeled source domain's knowledge to improve the model's discriminability on the unlabele…
Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation
Shengsen Wu, Liang Chen, Yihang Lou +4
In object re-identification (ReID), the development of deep learning techniques often involves model updates and deployment. It is unbearable to re-embedding and re-index with the…
Generalizable Person Re-identification with Relevance-aware Mixture of Experts
Yongxing Dai, Xiaotong Li, Jun Liu +2
Domain generalizable (DG) person re-identification (ReID) is a challenging problem because we cannot access any unseen target domain data during training. Almost all the existing D…
Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification
Yongxing Dai, Jun Liu, Yan Bai +2
Unsupervised domain adaptive (UDA) person re-identification (re-ID) is a challenging task due to the missing of labels for the target domain data. To handle this problem, some rece…
Key-Point Sequence Lossless Compression for Intelligent Video Analysis
Weiyao Lin, Xiaoyi He, Wenrui Dai +4
Feature coding has been recently considered to facilitate intelligent video analysis for urban computing. Instead of raw videos, extracted features in the front-end are encoded and…
Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics
Ling-Yu Duan, Jiaying Liu, Wenhan Yang +2
Video coding, which targets to compress and reconstruct the whole frame, and feature compression, which only preserves and transmits the most critical information, stand at two end…
Towards Coding for Human and Machine Vision: A Scalable Image Coding Approach
Yueyu Hu, Shuai Yang, Wenhan Yang +2
The past decades have witnessed the rapid development of image and video coding techniques in the era of big data. However, the signal fidelity-driven coding pipeline design limits…
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal
Sifeng Xia, Kunchangtai Liang, Wenhan Yang +2
In this paper, we study a new problem arising from the emerging MPEG standardization effort Video Coding for Machine (VCM), which aims to bridge the gap between visual feature comp…
Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm
Yihang Lou, Ling-Yu Duan, Yong Luo +4
The digital retina in smart cities is to select what the City Eye tells the City Brain, and convert the acquired visual data from front-end visual sensors to features in an intelli…
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
Jun Liu, Amir Shahroudy, Mauricio Perez +3
Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition. The existing depth-…
SPLINE-Net: Sparse Photometric Stereo through Lighting Interpolation and Normal Estimation Networks
Qian Zheng, Yiming Jia, Boxin Shi +3
This paper solves the Sparse Photometric stereo through Lighting Interpolation and Normal Estimation using a generative Network (SPLINE-Net). SPLINE-Net contains a lighting interpo…
Skeleton-Based Online Action Prediction Using Scale Selection Network
Jun Liu, Amir Shahroudy, Gang Wang +2
Action prediction is to recognize the class label of an ongoing activity when only a part of it is observed. In this paper, we focus on online action prediction in streaming 3D ske…
Exploring Object Relation in Mean Teacher for Cross-Domain Detection
Qi Cai, Yingwei Pan, Chong-Wah Ngo +3
Rendering synthetic data (e.g., 3D CAD-rendered images) to generate annotations for learning deep models in vision tasks has attracted increasing attention in recent years. However…
Towards Accurate One-Stage Object Detection with AP-Loss
Kean Chen, Jianguo Li, Weiyao Lin +6
One-stage object detectors are trained by optimizing classification-loss and localization-loss simultaneously, with the former suffering much from extreme foreground-background cla…
Face Image Reflection Removal
Renjie Wan, Boxin Shi, Haoliang Li +2
Face images captured through the glass are usually contaminated by reflections. The non-transmitted reflections make the reflection removal more challenging than for general scenes…
Feature Boosting Network For 3D Pose Estimation
Jun Liu, Henghui Ding, Amir Shahroudy +4
In this paper, a feature boosting network is proposed for estimating 3D hand pose and 3D body pose from a single RGB image. In this method, the features learned by the convolutiona…
Intermediate Deep Feature Compression: the Next Battlefield of Intelligent Sensing
Zhuo Chen, Weisi Lin, Shiqi Wang +2
The recent advances of hardware technology have made the intelligent analysis equipped at the front-end with deep learning more prevailing and practical. To better enable the intel…
CRRN: Multi-Scale Guided Concurrent Reflection Removal Network
Renjie Wan, Boxin Shi, Ling-Yu Duan +2
Removing the undesired reflections from images taken through the glass is of broad application to various computer vision tasks. Non-learning based methods utilize different handcr…