Papers Video Denoising
“Video Denoising” 태그가 달린 논문 104편 · 필터 해제
What Makes World Action Models Generalize? An Empirical Study of Test-Time Future Modeling
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 during inference is disputed: Explicit WAM…
Video DenoisingAdaptive-WAM: Quality-Guided Early-Exit Planning from Intermediate Video-Diffusion Features
Large video diffusion models provide rich spatiotemporal priors for autonomous driving, but existing world-action models often inherit the cost of iterative future-video generation even though deployment only requires an…
Autonomous DrivingVideo GenerationVideo DenoisingUNIVERSE: Unified Video Action Models for Autonomous Driving with Flexible Mask-Modulated Modality Generation
World Action Models (WAMs) have shown strong potential for improving action generalization in autonomous driving by using future video prediction as dense supervision for scene dynamics and temporal causality. However, i…
Autonomous DrivingVideo PredictionVideo DenoisingNext Forcing: Causal World Modeling with Multi-Chunk Prediction
Autoregressive video generation has emerged as a powerful paradigm for World Action Models (WAMs). However, existing approaches suffer from slow training convergence and limited converged accuracy, particularly at high f…
Video GenerationVideo DenoisingSANTS: A State-Adaptive Scheduler for World Action Models
World Action Models (WAMs) improve robot manipulation by using video-based future representations to condition action generation. In pixel-space WAMs, however, the best action condition is not necessarily the fully denoi…
Robot ManipulationVideo DenoisingStreamChar: Long-Horizon Streaming Character Audio-Video Generation with Decoupled Orchestration
Real-time streaming joint audio-video generation for character animation requires a generator to speak the requested transcript, maintain visual identity across chunks, and run within a strict playback budget. These requ…
Video GenerationVideo DenoisingBaton: Explicit Semantic Blueprints for Joint Video-Audio Generation
Current open-source diffusion models struggle to generate stable and synchronized audio-visual content, particularly in scenarios demanding complex semantic reasoning. The root cause is that existing methods rely on coar…
Audio GenerationVideo DenoisingUHD-GPGNet: UHD Video Denoising via Gaussian-Process-Guided Local Spatio-Temporal Modeling
Ultra-high-definition (UHD) video denoising requires simultaneously suppressing complex spatio-temporal degradations, preserving fine textures and chromatic stability, and maintaining efficient full-resolution 4K deploym…
Object DetectionVideo DenoisingFast-WAM: Do World Action Models Need Test-time Future Imagination?
World Action Models (WAMs) have emerged as a promising alternative to Vision-Language-Action (VLA) models for embodied control because they explicitly model how visual observations may evolve under action. Most existing …
Video PredictionVideo DenoisingFrames2Residual: Spatiotemporal Decoupling for Self-Supervised Video Denoising
Self-supervised video denoising methods typically extend image-based frameworks into the temporal dimension, yet they often struggle to integrate inter-frame temporal consistency with intra-frame spatial specificity. Exi…
Video DenoisingA Constrained Optimization Perspective of Unrolled Transformers
We introduce a constrained optimization framework for training transformers that behave like optimization descent algorithms. Specifically, we enforce layerwise descent constraints on the objective function and replace s…
Text ClassificationVideo DenoisingPocketDVDNet: Realtime Video Denoising for Real Camera Noise
Live video denoising under realistic, multi-component sensor noise remains challenging for applications such as autofocus, autonomous driving, and surveillance. We propose PocketDVDNet, a lightweight video denoiser devel…
Knowledge DistillationAutonomous DrivingModel CompressionVideo DenoisingDarkVRAI: Capture-Condition Conditioning and Burst-Order Selective Scan for Low-light RAW Video Denoising
Low-light RAW video denoising is a fundamentally challenging task due to severe signal degradation caused by high sensor gain and short exposure times, which are inherently limited by video frame rate requirements. To ad…
Image DenoisingVideo DenoisingAIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Results
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 exploiting temporal redundancy while operating …
Image ManipulationVideo DenoisingDenoise-then-Retrieve: Text-Conditioned Video Denoising for Video Moment Retrieval
Current text-driven Video Moment Retrieval (VMR) methods encode all video clips, including irrelevant ones, disrupting multimodal alignment and hindering optimization. To this end, we propose a denoise-then-retrieve para…
Moment RetrievalVideo DenoisingMotionPro: A Precise Motion Controller for Image-to-Video Generation
Animating images with interactive motion control has garnered popularity for image-to-video (I2V) generation. Modern approaches typically rely on large Gaussian kernels to extend motion trajectories as condition without …
DenoisingImage to Video GenerationMotion SynthesisVideo Denoising+1CIM-NET: A Video Denoising Deep Neural Network Model Optimized for Computing-in-Memory Architectures
While deep neural network (DNN)-based video denoising has demonstrated significant performance, deploying state-of-the-art models on edge devices remains challenging due to stringent real-time and energy efficiency requi…
DenoisingVideo DenoisingUniFlowRestore: A General Video Restoration Framework via Flow Matching and Prompt Guidance
Video imaging is often affected by complex degradations such as blur, noise, and compression artifacts. Traditional restoration methods follow a "single-task single-model" paradigm, resulting in poor generalization and h…
DenoisingSSIMVideo DenoisingVideo RestorationClassic Video Denoising in a Machine Learning World: Robust, Fast, and Controllable
Denoising is a crucial step in many video processing pipelines such as in interactive editing, where high quality, speed, and user control are essential. While recent approaches achieve significant improvements in denois…
DenoisingVideo DenoisingDynamiCtrl: Rethinking the Basic Structure and the Role of Text for High-quality Human Image Animation
With diffusion transformer (DiT) excelling in video generation, its use in specific tasks has drawn increasing attention. However, adapting DiT for pose-guided human image animation faces two core challenges: (a) existin…
DenoisingHuman AnimationImage AnimationVideo Denoising+1