17 citations · 21 across the 10 of their papers we have counts for
10 papers
InstructVVT: Instruction-Driven Video Virtual Try-On without Auxiliary Spatial Priors
Dingbao Shao, Song Wu, Xinyu Chen +18
Video virtual try-on is a highly constrained editing task requiring the precise replacement of a target person's clothing while strictly preserving the original video's spatial str…
Bridging Degradation Discrimination and Generation for Universal Image Restoration
JiaKui Hu, Zhengjian Yao, Lujia Jin +1
Universal image restoration is a critical task in low-level vision, requiring the model to remove various degradations from low-quality images to produce clean images with rich det…
Universal Image Restoration Pre-training via Masked Degradation Classification
JiaKui Hu, Zhengjian Yao, Lujia Jin +2
This study introduces a Masked Degradation Classification Pre-Training method (MaskDCPT), designed to facilitate the classification of degradation types in input images, leading to…
Enhancing Image Restoration Transformer via Adaptive Translation Equivariance
JiaKui Hu, Zhengjian Yao, Lujia Jin +2
Translation equivariance is a fundamental inductive bias in image restoration, ensuring that translated inputs produce translated outputs. Attention mechanisms in modern restoratio…
Universal Image Restoration Pre-training via Degradation Classification
JiaKui Hu, Lujia Jin, Zhengjian Yao +1
This paper proposes the Degradation Classification Pre-Training (DCPT), which enables models to learn how to classify the degradation type of input images for universal image resto…
Scribble Hides Class: Promoting Scribble-Based Weakly-Supervised Semantic Segmentation with Its Class Label
Xinliang Zhang, Lei Zhu, Hangzhou He +2
Scribble-based weakly-supervised semantic segmentation using sparse scribble supervision is gaining traction as it reduces annotation costs when compared to fully annotated alterna…
Multi-level Asymmetric Contrastive Learning for Volumetric Medical Image Segmentation Pre-training
Shuang Zeng, Lei Zhu, Xinliang Zhang +10
Medical image segmentation is a fundamental yet challenging task due to the arduous process of acquiring large volumes of high-quality labeled data from experts. Contrastive learni…
One-Pot Multi-Frame Denoising
Lujia Jin, Shi Zhao, Lei Zhu +2
The performance of learning-based denoising largely depends on clean supervision. However, it is difficult to obtain clean images in many scenes. On the contrary, the capture of mu…
Bagging Regional Classification Activation Maps for Weakly Supervised Object Localization
Lei Zhu, Qian Chen, Lujia Jin +2
Classification activation map (CAM), utilizing the classification structure to generate pixel-wise localization maps, is a crucial mechanism for weakly supervised object localizati…
Background-aware Classification Activation Map for Weakly Supervised Object Localization
Lei Zhu, Qi She, Qian Chen +9
Weakly supervised object localization (WSOL) relaxes the requirement of dense annotations for object localization by using image-level classification masks to supervise its learnin…