arXiv Computer Vision
CLEAR: Color-Texture Latent Alignment for Single Image Reflection Removal
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arXiv AI
Aug 13
From Synthesis to Removal: Physics-Grounded Reflection Simulation and Diffusion-Based Video Dereflection
arXiv:2608. 11562v1 Announce Type: cross Abstract: Videos captured through glass often contain reflections that degrade visual quality and interfere with downstream vision tasks.
arXiv Computer Vision
Oct 21
Efficient One-Step Diffusion Restoration Model with Compact Token Compression and Linear Attention
The paper introduces SANA‑SR, an efficient one‑step diffusion restoration framework for real‑world image super‑resolution. It uses a deep compression autoencoder to reduce latent tokens by a 32× ratio, preserving essential structures and textures, and applies a linear‑attention DiT with LoRA fine‑tuning for linear‑complexity token mixing. Experiments show competitive or superior performance on benchmark datasets, and the pruned model runs in 0.019 s with 407.95 G MACs and 344 M parameters, indicating strong potential for mobile deployment.
arXiv Computer Vision
Oct 23
GLOW-FM: Efficient Generative Low-Light Image Enhancement with One-Step Latent Flow Matching
GLOW-FM is a one‑step latent flow‑matching framework designed for efficient generative low‑light image enhancement (LLIE). It operates in the latent space of a frozen Tiny‑VAE, using Terminal Velocity Matching (TVM) to achieve high‑quality enhancement with a single function evaluation. Experiments on real‑world benchmarks show competitive image quality, strong cross‑dataset generalization, and low computational cost (34 GFLOPs for the small variant).
arXiv Computer Vision
Sep 28
IDM-Net: A Lightweight Illumination-Decoupled Modulation Network for Low-Light Image Enhancement
IDM-Net is a lightweight Illumination-Decoupled Modulation Network designed for low-light image enhancement. It uses a dual-encoder architecture: a structure encoder extracts multi-scale appearance features from the RGB image, while a lightweight illumination encoder learns illumination priors from the decoupled luminance channel. An Illumination-Guided Modulation module injects these priors into the decoder via spatially adaptive affine modulation, and a Feature Refinement Block progressively suppresses artifacts and recovers fine details, achieving competitive performance on standard benchmarks with good balance between quality and efficiency.
arXiv Computer Vision
Aug 21
Unwarping the Lens: A Physics-Grounded Approach to Video Glasses Removal
arXiv:2608. 20212v1 Announce Type: new Abstract: High-fidelity removal of eyeglasses from video is a major challenge in facial attribute editing, as the underlying facial geometry is often obscured by complex refractive distortions and view-dependent specular reflections.
arXiv Computer Vision
1d ago
Unaligned Image Guided Denoising via Cross-modal Conditional Flow Matching
arXiv:2611.06422v1 Announce Type: new Abstract: This work presents UGD-FM, a novel unaligned image guided denoising framework based on cross-modal conditional flow matching. Unlike previous approache...