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20242026
most citedMVAR: Visual Autoregressive Modeling with Scale and Spatial Markovian Conditioning

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cs.CV2026

Advanced Pixel Diffusion Model with Guided Sparse Global Refinement

Weiyi You, Jinhua Zhang, Xingyu Zhou +3

Pixel-space diffusion has recently emerged as a promising direction for high-fidelity image generation by modeling images directly in the original pixel domain. However, pixel-spac…

cs.CV2026

Beyond Token-Level Cross-Entropy: Fréchet Distributional Post-Training for Autoregressive Image Generation

Jinhua Zhang, Yisong Lin, Wei Long +1

Autoregressive image generators are commonly pretrained with token-level cross-entropy under teacher forcing, yet evaluated by the distributional quality of decoded images. This cr…

cs.CV2026

Perceiving Better Moments: Cover Frame Reselection and Enhancement for Live Photos with the Live2K Dataset

Junyu Lou, Kai Chen, Weiyi You +3

Modern smartphones capture Live Photos, short video bursts surrounding a still image, offering a dynamic and engaging photographic experience. However, the cover photo and video co…

cs.CV2026

Taming Sampling Perturbations with Variance Expansion Loss for Latent Diffusion Models

Qifan Li, Xingyu Zhou, Jinhua Zhang +2

Latent diffusion models have emerged as the dominant framework for high-fidelity and efficient image generation, owing to their ability to learn diffusion processes in compact late…

cs.CV2026

ATD: Improved Transformer with Adaptive Token Dictionary for Image Restoration

Leheng Zhang, Wei Long, Yawei Li +3

Recently, Transformers have gained significant popularity in image restoration tasks such as image super-resolution and denoising, owing to their superior performance. However, bal…

cs.CV2026

From Local Windows to Adaptive Candidates via Individualized Exploratory: Rethinking Attention for Image Super-Resolution

Chunyu Meng, Wei Long, Shuhang Gu

Single Image Super-Resolution (SISR) is a fundamental computer vision task that aims to reconstruct a high-resolution (HR) image from a low-resolution (LR) input. Transformer-based…