61 citations · 198 across the 25 of their papers we have counts for
22 papers · 1 filter
AccFlow: Backward Accumulation for Long-Range Optical Flow
Guangyang Wu, Xiaohong Liu, Kunming Luo +6
Recent deep learning-based optical flow estimators have exhibited impressive performance in generating local flows between consecutive frames. However, the estimation of long-range…
Dissecting Arbitrary-scale Super-resolution Capability from Pre-trained Diffusion Generative Models
Ruibin Li, Qihua Zhou, Song Guo +5
Diffusion-based Generative Models (DGMs) have achieved unparalleled performance in synthesizing high-quality visual content, opening up the opportunity to improve image super-resol…
Unsupervised Video Anomaly Detection for Stereotypical Behaviours in Autism
Jiaqi Gao, Xinyang Jiang, Yuqing Yang +2
Monitoring and analyzing stereotypical behaviours is important for early intervention and care taking in Autism Spectrum Disorder (ASD). This paper focuses on automatically detecti…
Attentive Mask CLIP
Yifan Yang, Weiquan Huang, Yixuan Wei +8
Image token removal is an efficient augmentation strategy for reducing the cost of computing image features. However, this efficient augmentation strategy has been found to adverse…
Learning Domain Invariant Prompt for Vision-Language Models
Cairong Zhao, Yubin Wang, Xinyang Jiang +4
Prompt learning is one of the most effective and trending ways to adapt powerful vision-language foundation models like CLIP to downstream datasets by tuning learnable prompt vecto…
Invisible Backdoor Attack with Dynamic Triggers against Person Re-identification
Wenli Sun, Xinyang Jiang, Shuguang Dou +4
In recent years, person Re-identification (ReID) has rapidly progressed with wide real-world applications, but also poses significant risks of adversarial attacks. In this paper, w…
Online Video Super-Resolution with Convolutional Kernel Bypass Graft
Jun Xiao, Xinyang Jiang, Ningxin Zheng +5
Deep learning-based models have achieved remarkable performance in video super-resolution (VSR) in recent years, but most of these models are less applicable to online video applic…
Towards Privacy-Preserving Person Re-identification via Person Identify Shift
Shuguang Dou, Xinyang Jiang, Qingsong Zhao +2
Recently privacy concerns of person re-identification (ReID) raise more and more attention and preserving the privacy of the pedestrian images used by ReID methods become essential…
RendNet: Unified 2D/3D Recognizer With Latent Space Rendering
Ruoxi Shi, Xinyang Jiang, Caihua Shan +2
Vector graphics (VG) have been ubiquitous in our daily life with vast applications in engineering, architecture, designs, etc. The VG recognition process of most existing methods i…
Privacy-preserving Online AutoML for Domain-Specific Face Detection
Chenqian Yan, Yuge Zhang, Quanlu Zhang +4
Despite the impressive progress of general face detection, the tuning of hyper-parameters and architectures is still critical for the performance of a domain-specific face detector…
Domain Generalization using Pretrained Models without Fine-tuning
Ziyue Li, Kan Ren, Xinyang Jiang +3
Fine-tuning pretrained models is a common practice in domain generalization (DG) tasks. However, fine-tuning is usually computationally expensive due to the ever-growing size of pr…
Recognizing Vector Graphics without Rasterization
Xinyang Jiang, Lu Liu, Caihua Shan +3
In this paper, we consider a different data format for images: vector graphics. In contrast to raster graphics which are widely used in image recognition, vector graphics can be sc…
Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision
Bo Li, Xinyang Jiang, Donglin Bai +6
The energy consumption of deep learning models is increasing at a breathtaking rate, which raises concerns due to potential negative effects on carbon neutrality in the context of…
Ask&Confirm: Active Detail Enriching for Cross-Modal Retrieval with Partial Query
Guanyu Cai, Jun Zhang, Xinyang Jiang +7
Text-based image retrieval has seen considerable progress in recent years. However, the performance of existing methods suffers in real life since the user is likely to provide an…
Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search
Chenyang Gao, Guanyu Cai, Xinyang Jiang +6
Text-based person search aims at retrieving target person in an image gallery using a descriptive sentence of that person. It is very challenging since modal gap makes effectively…
One for More: Selecting Generalizable Samples for Generalizable ReID Model
Enwei Zhang, Xinyang Jiang, Hao Cheng +7
Current training objectives of existing person Re-IDentification (ReID) models only ensure that the loss of the model decreases on selected training batch, with no regards to the p…
Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion
Jinpeng Wang, Yuting Gao, Ke Li +5
One significant factor we expect the video representation learning to capture, especially in contrast with the image representation learning, is the object motion. However, we foun…
Devil's in the Details: Aligning Visual Clues for Conditional Embedding in Person Re-Identification
Fufu Yu, Xinyang Jiang, Yifei Gong +5
Although Person Re-Identification has made impressive progress, difficult cases like occlusion, change of view-pointand similar clothing still bring great challenges. Besides overa…
Do Not Disturb Me: Person Re-identification Under the Interference of Other Pedestrians
Shizhen Zhao, Changxin Gao, Jun Zhang +7
In the conventional person Re-ID setting, it is widely assumed that cropped person images are for each individual. However, in a crowded scene, off-shelf-detectors may generate bou…
Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification
Zhihui Zhu, Xinyang Jiang, Feng Zheng +4
Although great progress in supervised person re-identification (Re-ID) has been made recently, due to the viewpoint variation of a person, Re-ID remains a massive visual challenge.…
Rethinking Temporal Fusion for Video-based Person Re-identification on Semantic and Time Aspect
Xinyang Jiang, Yifei Gong, Xiaowei Guo +5
Recently, the research interest of person re-identification (ReID) has gradually turned to video-based methods, which acquire a person representation by aggregating frame features…
Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training
Feng Zheng, Cheng Deng, Xing Sun +5
Most existing Re-IDentification (Re-ID) methods are highly dependent on precise bounding boxes that enable images to be aligned with each other. However, due to the challenging pra…