2 citations · 7 across the 33 of their papers we have counts for
39 papers
DuplexBridge: Coordinating Understanding and Generation for Unified Image Editing
Yidi Liu, Jie Xiao, Chaojie Mao +2
Complex image editing requires faithful task interpretation and accurate execution, but a failed edit does not reveal which responsibility failed. We present DuplexBridge, which us…
RSIgen: Reciprocal Self-Improvement for Agentic Visual Generation
Yidi Liu, Haozhe Wang, Jie Xiao +3
Agentic visual generation produces experience that can improve the native understanding (agent) and generation roles of a unified multimodal backbone, but task success alone does n…
MaskSense: Confronting the Visual Exploration Trap in Masked Image Generation
Yawen Shao, Jie Xiao, Kai Zhu +6
Reinforcement learning (RL) has shown strong potential for aligning generative models with human intent, but adapting RL to masked generative models (MGMs) remains largely underexp…
What Makes World Action Models Generalize? An Empirical Study of Test-Time Future Modeling
Renping Zhou, Zanlin Ni, Zihao Fan +8
World action models (WAMs) predict the future alongside actions during training. Due to the heavy computation cost of video denoising, whether the future must still be generated du…
Code Plans, Diffusion Renders: Open-Ended Generative World Modeling
Zixun Fang, Yawen Shao, Kai Zhu +7
We introduce \textbf{CoDeR}, a new paradigm for world modeling. Unlike existing video world models that implicitly represent world dynamics through visual observations, our system…
LiAuto-MindViT: A Hybrid Vision Backbone with Adaptive Bidirectional Mamba
Lifu Mu, Shuai Chen, Wen Zheng +7
While Mamba-based models have shown strong potential for long sequence modeling, adapting them to vision is challenging due to the requirement of local neighborhood correlations an…
OmniVR: Audio-Video Conditional Generation for Archival Footage Restoration
Xin Lu, Zihao Fan, Mingchen Zhong +4
Archival footage often suffers from coupled visual and acoustic degradations, yet most restoration systems process the two modalities separately. To address this problem, we presen…
Back on Track: Aligning Rewards and States for Reasoning in Diffusion Large Language Models
Yawen Shao, Jie Xiao, Kai Zhu +6
Reinforcement learning (RL) holds immense promise for enhancing the reasoning capabilities of diffusion large language models (dLLMs). However, progress is fundamentally constraine…
Event-Illumination Collaborative Low-light Image Enhancement with a High-resolution Real-world Dataset
Senyan Xu, Zhijing Sun, Kean Liu +5
Event-based low-light image enhancement (LIE) methods mainly focus on incorporating high dynamic range (HDR) information from events while overlooking the essential global illumina…
EventGait: Towards Robust Gait Recognition with Event Streams
Senyan Xu, Shuai Chen, Chuanfu Shen +4
Gait recognition enables non-intrusive, privacy-preserving identification but suffers in uncontrolled environments due to illumination and motion sensitivity of conventional camera…
IR-Flow: Bridging Discriminative and Generative Image Restoration via Rectified Flow
Zihao Fan, Xin Lu, Jie Xiao +3
In image restoration, single-step discriminative mappings often lack fine details via expectation learning, whereas generative paradigms suffer from inefficient multi-step sampling…
GS-STVSR: Ultra-Efficient Continuous Spatio-Temporal Video Super-Resolution via 2D Gaussian Splatting
Mingyu Shi, Xin Di, Long Peng +8
Continuous Spatio-Temporal Video Super-Resolution (C-STVSR) aims to simultaneously enhance the spatial resolution and frame rate of videos by arbitrary scale factors, offering grea…
The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview
Jiatong Li, Zheng Chen, Kai Liu +91
This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes. The challenge…
Bird-SR: Bidirectional Reward-Guided Diffusion for Real-World Image Super-Resolution
Zihao Fan, Xin Lu, Yidi Liu +4
Powered by multimodal text-to-image priors, diffusion-based super-resolution excels at synthesizing intricate details; however, models trained on synthetic low-resolution (LR) and…
Iterative Inference-time Scaling with Adaptive Frequency Steering for Image Super-Resolution
Hexin Zhang, Dong Li, Jie Huang +3
Diffusion models have become a leading paradigm for image super-resolution (SR), but existing methods struggle to guarantee both the high-frequency perceptual quality and the low-f…
FinPercep-RM: A Fine-grained Reward Model and Co-evolutionary Curriculum for RL-based Real-world Super-Resolution
Yidi Liu, Zihao Fan, Jie Huang +6
Reinforcement Learning with Human Feedback (RLHF) has proven effective in image generation field guided by reward models to align human preferences. Motivated by this, adapting RLH…
CompEvent: Complex-valued Event-RGB Fusion for Low-light Video Enhancement and Deblurring
Mingchen Zhong, Xin Lu, Dong Li +4
Low-light video deblurring poses significant challenges in applications like nighttime surveillance and autonomous driving due to dim lighting and long exposures. While event camer…
Latent Harmony: Synergistic Unified UHD Image Restoration via Latent Space Regularization and Controllable Refinement
Yidi Liu, Xueyang Fu, Jie Huang +5
Ultra-High Definition (UHD) image restoration faces a trade-off between computational efficiency and high-frequency detail retention. While Variational Autoencoders (VAEs) improve…
VisionSelector: End-to-End Learnable Visual Token Compression for Efficient Multimodal LLMs
Jiaying Zhu, Yurui Zhu, Xin Lu +5
Multimodal Large Language Models (MLLMs) encounter significant computational and memory bottlenecks from the massive number of visual tokens generated by high-resolution images or…
AIM 2025 challenge on Inverse Tone Mapping Report: Methods and Results
Chao Wang, Francesco Banterle, Bin Ren +25
This paper presents a comprehensive review of the AIM 2025 Challenge on Inverse Tone Mapping (ITM). The challenge aimed to push forward the development of effective ITM algorithms…
AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
George Ciubotariu, Florin-Alexandru Vasluianu, Zhuyun Zhou +44
This paper presents a comprehensive review of the AIM 2025 High FPS Non-Uniform Motion Deblurring Challenge, highlighting the proposed solutions and final results. The objective of…
AIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Results
Alexander Yakovenko, George Chakvetadze, Ilya Khrapov +17
This paper reviews the AIM 2025 (Advances in Image Manipulation) Low-Light RAW Video Denoising Challenge. The task is to develop methods that denoise low-light RAW video by exploit…
RobustGS: Unified Boosting of Feedforward 3D Gaussian Splatting under Low-Quality Conditions
Anran Wu, Long Peng, Xin Di +6
Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimi…
PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation
Kunyu Wang, Xueyang Fu, Yuanfei Bao +4
Continual Test-Time Adaptation (CTTA) aims to online adapt a pre-trained model to changing environments during inference. Most existing methods focus on exploiting target data, whi…