1 citations · 7 across the 42 of their papers we have counts for
45 papers
PAPT++: Risk-Aware Adversarial Tuning and Generation for Single Domain Generalization
Zhipeng Xu, De Cheng, Xinyang Jiang +5
Single domain generalization (SDG) aims to learn a model from one labeled source domain that generalizes to unseen target domains. A common strategy is to enrich the source distrib…
Efficient Difficulty-Aware Dynamic Routing for Diffusion-Based Real-World Image Super-Resolution
Xue Wu, Kang Zhao, Kafeng Wang +4
Diffusion-based methods have achieved impressive performance in real-world image super-resolution (Real-ISR) by leveraging large pre-trained stable diffusion (SD) models as powerfu…
Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection
Mingyue Zeng, De Cheng, Zhipeng Xu +3
Incremental object detection (IOD) aims to extend detectors to new categories while retaining previously acquired knowledge. Existing methods often adopt a class incremental learni…
Adversarial Domain Prompt Tuning and Generation for Single Domain Generalization
Zhipeng Xu, De Cheng, Xinyang Jiang +3
Single domain generalization (SDG) aims to learn a robust model, which could perform well on many unseen domains while there is only one single domain available for training. One o…
Bridging Data Trials and Task Barriers: A Unified Framework for Sketch Biometric Identification
Decheng Liu, Bin Hu, Xinbo Gao +4
Different from existing cross-modality identification tasks (e.g., heterogeneous face recognition, sketch re-identification, etc.), we introduce a novel yet practical setting for t…
Task-Driven Subspace Decomposition for Knowledge Sharing and Isolation in LoRA-based Continual Learning
Lingfeng He, De Cheng, Huaijie Wang +3
Continual Learning (CL) requires models to sequentially adapt to new tasks without forgetting old knowledge. Recently, Low-Rank Adaptation (LoRA), a representative Parameter-Effici…
Mixture of Ranks with Degradation-Aware Routing for One-Step Real-World Image Super-Resolution
Xiao He, Zhijun Tu, Kun Cheng +4
The demonstrated success of sparsely-gated Mixture-of-Experts (MoE) architectures, exemplified by models such as DeepSeek and Grok, has motivated researchers to investigate their a…
DermINO: Hybrid Pretraining for a Versatile Dermatology Foundation Model
Jingkai Xu, De Cheng, Xiangqian Zhao +27
Skin diseases impose a substantial burden on global healthcare systems, driven by their high prevalence (affecting up to 70% of the population), complex diagnostic processes, and a…
Hierarchical Identity Learning for Unsupervised Visible-Infrared Person Re-Identification
Haonan Shi, Yubin Wang, De Cheng +3
Unsupervised visible-infrared person re-identification (USVI-ReID) aims to learn modality-invariant image features from unlabeled cross-modal person datasets by reducing the modali…
CKAA: Cross-subspace Knowledge Alignment and Aggregation for Robust Continual Learning
Lingfeng He, De Cheng, Zhiheng Ma +4
Continual Learning (CL) empowers AI models to continuously learn from sequential task streams. Recently, parameter-efficient fine-tuning (PEFT)-based CL methods have garnered incre…
Prompt Disentanglement via Language Guidance and Representation Alignment for Domain Generalization
De Cheng, Zhipeng Xu, Xinyang Jiang +3
Domain Generalization (DG) seeks to develop a versatile model capable of performing effectively on unseen target domains. Notably, recent advances in pre-trained Visual Foundation…
TeSG: Textual Semantic Guidance for Infrared and Visible Image Fusion
Mingrui Zhu, Xiru Chen, Xin Wei +2
Infrared and visible image fusion (IVF) aims to combine complementary information from both image modalities, producing more informative and comprehensive outputs. Recently, text-g…
A Knowledge-guided Adversarial Defense for Resisting Malicious Visual Manipulation
Dawei Zhou, Suzhi Gang, Decheng Liu +3
Malicious applications of visual manipulation have raised serious threats to the security and reputation of users in many fields. To alleviate these issues, adversarial noise-based…
Structure-Accurate Medical Image Translation via Dynamic Frequency Balance and Knowledge Guidance
Jiahua Xu, Dawei Zhou, Lei Hu +3
Multimodal medical images play a crucial role in the precise and comprehensive clinical diagnosis. Diffusion model is a powerful strategy to synthesize the required medical images.…
Pro2SAM: Mask Prompt to SAM with Grid Points for Weakly Supervised Object Localization
Xi Yang, Songsong Duan, Nannan Wang +1
Weakly Supervised Object Localization (WSOL), which aims to localize objects by only using image-level labels, has attracted much attention because of its low annotation cost in re…
Semantic-Aligned Learning with Collaborative Refinement for Unsupervised VI-ReID
De Cheng, Lingfeng He, Nannan Wang +2
Unsupervised visible-infrared person re-identification (USL-VI-ReID) seeks to match pedestrian images of the same individual across different modalities without human annotations f…
CSHNet: A Novel Information Asymmetric Image Translation Method
Xi Yang, Haoyuan Shi, Zihan Wang +2
Despite advancements in cross-domain image translation, challenges persist in asymmetric tasks such as SAR-to-Optical and Sketch-to-Instance conversions, which involve transforming…
iFADIT: Invertible Face Anonymization via Disentangled Identity Transform
Lin Yuan, Kai Liang, Xiong Li +3
Face anonymization aims to conceal the visual identity of a face to safeguard the individual's privacy. Traditional methods like blurring and pixelation can largely remove identify…
SA3DIP: Segment Any 3D Instance with Potential 3D Priors
Xi Yang, Xu Gu, Xingyilang Yin +1
The proliferation of 2D foundation models has sparked research into adapting them for open-world 3D instance segmentation. Recent methods introduce a paradigm that leverages superp…
Mamba-CL: Optimizing Selective State Space Model in Null Space for Continual Learning
De Cheng, Yue Lu, Lingfeng He +4
Continual Learning (CL) aims to equip AI models with the ability to learn a sequence of tasks over time, without forgetting previously learned knowledge. Recently, State Space Mode…
Effective Diffusion Transformer Architecture for Image Super-Resolution
Kun Cheng, Lei Yu, Zhijun Tu +7
Recent advances indicate that diffusion models hold great promise in image super-resolution. While the latest methods are primarily based on latent diffusion models with convolutio…
Knowledge-Enhanced Facial Expression Recognition with Emotional-to-Neutral Transformation
Hangyu Li, Yihan Xu, Jiangchao Yao +3
Existing facial expression recognition (FER) methods typically fine-tune a pre-trained visual encoder using discrete labels. However, this form of supervision limits to specify the…
One Step Diffusion-based Super-Resolution with Time-Aware Distillation
Xiao He, Huaao Tang, Zhijun Tu +8
Diffusion-based image super-resolution (SR) methods have shown promise in reconstructing high-resolution images with fine details from low-resolution counterparts. However, these a…
Foodfusion: A Novel Approach for Food Image Composition via Diffusion Models
Chaohua Shi, Xuan Wang, Si Shi +4
Food image composition requires the use of existing dish images and background images to synthesize a natural new image, while diffusion models have made significant advancements i…