most citedSCL: Towards Domain Generalization via Single-Temporal Multimodal Contrastive Learning for Remote Sensing Change Detection

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cs.CV20261 cited

SCL: Towards Domain Generalization via Single-Temporal Multimodal Contrastive Learning for Remote Sensing Change Detection

Qiangang Du, Jinlong Peng, Xu Chen +4

In recent years, change detection and anomaly detection models based on CNN and transformer have achieved remarkable success across various datasets based on paired data. However,…

cs.CV2026

PixelPonder: Dynamic Patch Adaptation for Enhanced Multi-Conditional Text-to-Image Generation

Yanjie Pan, Qingdong He, Zhengkai Jiang +9

Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control. However, existing ControlNet-like methods struggle…

cs.CV2026

PackForcing: Short Video Training Suffices for Long Video Sampling and Long Context Inference

Xiaofeng Mao, Shaohao Rui, Kaining Ying +4

Autoregressive video diffusion models have demonstrated remarkable progress, yet they remain bottlenecked by intractable linear KV-cache growth, temporal repetition, and compoundin…

cs.CV2025

Yume: An Interactive World Generation Model

Xiaofeng Mao, Shaoheng Lin, Zhen Li +7

Yume aims to use images, text, or videos to create an interactive, realistic, and dynamic world, which allows exploration and control using peripheral devices or neural signals. In…

cs.CV2025

UniCombine: Unified Multi-Conditional Combination with Diffusion Transformer

Haoxuan Wang, Jinlong Peng, Qingdong He +9

With the rapid development of diffusion models in image generation, the demand for more powerful and flexible controllable frameworks is increasing. Although existing methods can g…

cs.CV2025

Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation

Ying Jin, Jinlong Peng, Qingdong He +8

The performance of anomaly inspection in industrial manufacturing is constrained by the scarcity of anomaly data. To overcome this challenge, researchers have started employing ano…