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ArcAD: Anomaly-Rectified Calibration for Cold-Start Supervised Anomaly Detection
Ningning Han, Lei Fan, Jia Guo +5
The deployment of Industrial Anomaly Detection (IAD) in real-world manufacturing frequently encounters a challenging cold-start bottleneck, in which limited normal samples fail to…
MOJITO: Modal Joint Learning for Unified End-to-End Autonomous Driving
Zhijing Cheng, Xuancheng Zhang, Donglin Di +4
End-to-end autonomous driving systems commonly follow a cascaded two-stage pipeline where a perception stage compresses multi-modal sensor inputs into a compact context and a downs…
Straight-Path Flow Matching for Incomplete Multi-View Clustering
Yiteng Yuan, Junyan Wang, Zheyuan Liu +4
Incomplete Multi-View Clustering addresses the problem of clustering multi-modal data when certain views are missing. Recent end-to-end generative approaches leverage diffusion mod…
CogPortrait: Fine-Grained Eye-Region Control in Portrait Animation via Hierarchical Agent Planning
He Feng, Yongjia Ma, Donglin Di +2
Portrait animation methods have achieved substantial visual quality and lip synchronization, but fine-grained manipulation of the eye region still faces a trade-off between input g…
Chain of World: World Model Thinking in Latent Motion
Fuxiang Yang, Donglin Di, Lulu Tang +6
Vision-Language-Action (VLA) models are a promising path toward embodied intelligence, yet they often overlook the predictive and temporal-causal structure underlying visual dynami…
Visual Prompt-Agnostic Evolution
Junze Wang, Lei Fan, Dezheng Zhang +5
Visual Prompt Tuning (VPT) adapts a frozen Vision Transformer (ViT) to downstream tasks by inserting a small number of learnable prompt tokens into the token sequence at each layer…
EFDiT: Efficient Fine-grained Image Generation Using Diffusion Transformer Models
Kun Wang, Donglin Di, Tonghua Su +1
Diffusion models are highly regarded for their controllability and the diversity of images they generate. However, class-conditional generation methods based on diffusion models of…
Cross-Stain Contrastive Learning for Paired Immunohistochemistry and Histopathology Slide Representation Learning
Yizhi Zhang, Lei Fan, Zhulin Tao +4
Universal, transferable whole-slide image (WSI) representations are central to computational pathology. Incorporating multiple markers (e.g., immunohistochemistry, IHC) alongside H…
Global-Local Aware Scene Text Editing
Fuxiang Yang, Tonghua Su, Donglin Di +4
Scene Text Editing (STE) involves replacing text in a scene image with new target text while preserving both the original text style and background texture. Existing methods suffer…
GAOT: Generating Articulated Objects Through Text-Guided Diffusion Models
Hao Sun, Lei Fan, Donglin Di +1
Articulated object generation has seen increasing advancements, yet existing models often lack the ability to be conditioned on text prompts. To address the significant gap between…
ADNet: A Large-Scale and Extensible Multi-Domain Benchmark for Anomaly Detection Across 380 Real-World Categories
Hai Ling, Jia Guo, Zhulin Tao +6
Anomaly detection (AD) aims to identify defects using normal-only training data. Existing anomaly detection benchmarks (e.g., MVTec-AD with 15 categories) cover only a narrow range…
Dinomaly2: A Unified Framework for Unsupervised Image Anomaly Detection
Jia Guo, Shuai Lu, Lei Fan +9
Unsupervised anomaly detection (UAD) has evolved from specialized single-class models to unified multi-class models, yet existing multi-class models significantly underperform the…
DiTalker: A Unified DiT-based Framework for High-Quality and Speaking Styles Controllable Portrait Animation
He Feng, Yongjia Ma, Donglin Di +3
Portrait animation aims to synthesize talking videos from a static reference face, conditioned on audio and style frame cues (e.g., emotion and head poses), while ensuring precise…
Spatially Gene Expression Prediction using Dual-Scale Contrastive Learning
Mingcheng Qu, Yuncong Wu, Donglin Di +4
Spatial transcriptomics (ST) provides crucial insights into tissue micro-environments, but is limited to its high cost and complexity. As an alternative, predicting gene expression…
Memory-Augmented Incomplete Multimodal Survival Prediction via Cross-Slide and Gene-Attentive Hypergraph Learning
Mingcheng Qu, Guang Yang, Donglin Di +4
Multimodal pathology-genomic analysis is critical for cancer survival prediction. However, existing approaches predominantly integrate formalin-fixed paraffin-embedded (FFPE) slide…
Hypergraph Tversky-Aware Domain Incremental Learning for Brain Tumor Segmentation with Missing Modalities
Junze Wang, Lei Fan, Weipeng Jing +4
Existing methods for multimodal MRI segmentation with missing modalities typically assume that all MRI modalities are available during training. However, in clinical practice, some…
Multimodal Cancer Survival Analysis via Hypergraph Learning with Cross-Modality Rebalance
Mingcheng Qu, Guang Yang, Donglin Di +4
Multimodal pathology-genomic analysis has become increasingly prominent in cancer survival prediction. However, existing studies mainly utilize multi-instance learning to aggregate…
Adams Bashforth Moulton Solver for Inversion and Editing in Rectified Flow
Yongjia Ma, Donglin Di, Xuan Liu +4
Rectified flow models have achieved remarkable performance in image and video generation tasks. However, existing numerical solvers face a trade-off between fast sampling and high…
Tuning-Free Long Video Generation via Global-Local Collaborative Diffusion
Yongjia Ma, Junlin Chen, Donglin Di +6
Creating high-fidelity, coherent long videos is a sought-after aspiration. While recent video diffusion models have shown promising potential, they still grapple with spatiotempora…
DH-FaceVid-1K: A Large-Scale High-Quality Dataset for Face Video Generation
Donglin Di, He Feng, Wenzhang Sun +6
Human-centric generative models are becoming increasingly popular, giving rise to various innovative tools and applications, such as talking face videos conditioned on text or audi…
GRPose: Learning Graph Relations for Human Image Generation with Pose Priors
Xiangchen Yin, Donglin Di, Lei Fan +6
Recent methods using diffusion models have made significant progress in human image generation with various control signals such as pose priors. However, existing efforts are still…
ToCoAD: Two-Stage Contrastive Learning for Industrial Anomaly Detection
Yun Liang, Zhiguang Hu, Junjie Huang +3
Current unsupervised anomaly detection approaches perform well on public datasets but struggle with specific anomaly types due to the domain gap between pre-trained feature extract…