37 citations · 101 across the 15 of their papers we have counts for
15 papers
Learning to Synthesize Compatible Fashion Items Using Semantic Alignment and Collocation Classification: An Outfit Generation Framework
Dongliang Zhou, Haijun Zhang, Kai Yang +5
The field of fashion compatibility learning has attracted great attention from both the academic and industrial communities in recent years. Many studies have been carried out for…
Clarity ChatGPT: An Interactive and Adaptive Processing System for Image Restoration and Enhancement
Yanyan Wei, Zhao Zhang, Jiahuan Ren +5
The generalization capability of existing image restoration and enhancement (IRE) methods is constrained by the limited pre-trained datasets, making it difficult to handle agnostic…
DiffDance: Cascaded Human Motion Diffusion Model for Dance Generation
Qiaosong Qi, Le Zhuo, Aixi Zhang +4
When hearing music, it is natural for people to dance to its rhythm. Automatic dance generation, however, is a challenging task due to the physical constraints of human motion and…
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
Wenwen Yu, Chengquan Zhang, Haoyu Cao +24
Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, an…
Evolving Knowledge Mining for Class Incremental Segmentation
Zhihe Lu, Shuicheng Yan, Xinchao Wang
Class Incremental Semantic Segmentation (CISS) has been a trend recently due to its great significance in real-world applications. Although the existing CISS methods demonstrate re…
A Review of Deep Learning for Video Captioning
Moloud Abdar, Meenakshi Kollati, Swaraja Kuraparthi +8
Video captioning (VC) is a fast-moving, cross-disciplinary area of research that bridges work in the fields of computer vision, natural language processing (NLP), linguistics, and…
InceptionNeXt: When Inception Meets ConvNeXt
Weihao Yu, Pan Zhou, Shuicheng Yan +1
Inspired by the long-range modeling ability of ViTs, large-kernel convolutions are widely studied and adopted recently to enlarge the receptive field and improve model performance,…
MDTv2: Masked Diffusion Transformer is a Strong Image Synthesizer
Shanghua Gao, Pan Zhou, Ming-Ming Cheng +1
Despite its success in image synthesis, we observe that diffusion probabilistic models (DPMs) often lack contextual reasoning ability to learn the relations among object parts in a…
Contrastive Video Question Answering via Video Graph Transformer
Junbin Xiao, Pan Zhou, Angela Yao +4
We propose to perform video question answering (VideoQA) in a Contrastive manner via a Video Graph Transformer model (CoVGT). CoVGT's uniqueness and superiority are three-fold: 1)…
STPrivacy: Spatio-Temporal Privacy-Preserving Action Recognition
Ming Li, Xiangyu Xu, Hehe Fan +7
Existing methods of privacy-preserving action recognition (PPAR) mainly focus on frame-level (spatial) privacy removal through 2D CNNs. Unfortunately, they have two major drawbacks…
Position-guided Text Prompt for Vision-Language Pre-training
Alex Jinpeng Wang, Pan Zhou, Mike Zheng Shou +1
Vision-Language Pre-Training (VLP) has shown promising capabilities to align image and text pairs, facilitating a broad variety of cross-modal learning tasks. However, we observe t…
Seeing Through the Noisy Dark: Towards Real-world Low-Light Image Enhancement and Denoising
Jiahuan Ren, Zhao Zhang, Richang Hong +3
Low-light image enhancement (LLIE) aims at improving the illumination and visibility of dark images with lighting noise. To handle the real-world low-light images often with heavy…
Decoupled Cross-Scale Cross-View Interaction for Stereo Image Enhancement in The Dark
Huan Zheng, Zhao Zhang, Jicong Fan +3
Low-light stereo image enhancement (LLSIE) is a relatively new task to enhance the quality of visually unpleasant stereo images captured in dark condition. However, current methods…
Towards Sustainable Self-supervised Learning
Shanghua Gao, Pan Zhou, Ming-Ming Cheng +1
Although increasingly training-expensive, most self-supervised learning (SSL) models have repeatedly been trained from scratch but not fully utilized, since only a few SOTAs are em…
Towards Feature Distribution Alignment and Diversity Enhancement for Data-Free Quantization
Yangcheng Gao, Zhao Zhang, Richang Hong +3
To obtain lower inference latency and less memory footprint of deep neural networks, model quantization has been widely employed in deep model deployment, by converting the floatin…