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20222026
most citedMasked Modeling for Self-supervised Representation Learning on Vision and Beyond

7 citations · 20 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

FROD: Feature Matching Residual Denoising Oracle Bone Decipher

Yanbin Hou, Biao Xiong, Guojun Xu +4

Oracle bone script (OBS), one of the earliest Chinese writing systems, plays an important role in the study of Chinese etymology. Traditional decipherment relies heavily on domain…

cs.CV2026

Learning Video Dynamics with Predictive Differentiable Rendering

Yujin Tang, Tian Zhou, Xin Lin +5

How to accurately predict a high-fidelity future world? While the visual world is inherently continuous, existing deterministic video prediction models operate in discrete pixel sp…

cs.CV2026

MergeTok: Unified Continuous and Discrete Visual Tokenization via Token Merging

Luyuan Zhang, Siyuan Li, Zedong Wang +7

Most visual tokenizers for image generation are bifurcated into two families with complementary limitations: continuous VAEs offer high-fidelity reconstruction but suffer from dens…

cs.CV2026

Distributed Image Compression with Multimodal Side Information at Extremely Low Bitrates

Guojun Xu, Mingyang Zhang, Jianwen Xiang +3

Distributed Image Compression (DIC) is crucial for multi-view transmission, especially when operating at extremely low bitrates (< 0.1 bpp). Its core challenge is effectively utili…

cs.CV2026

RankE: End-to-End Post-Training for Discrete Text-to-Image Generation with Decoder Co-Evolution

Siyong Jian, Siyuan Li, Luyuan Zhang +5

Discrete autoregressive (AR) text-to-image (T2I) models pair a VQ tokenizer with an AR policy, and current post-training pipelines optimize only the policy while keeping the VQ dec…

cs.CV2025

MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization

Siyuan Li, Luyuan Zhang, Zedong Wang +8

Masked Image Modeling (MIM) with Vector Quantization (VQ) has achieved great success in both self-supervised pre-training and image generation. However, most existing methods strug…

cs.CV2024★ 7 cited

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond

Siyuan Li, Luyuan Zhang, Zedong Wang +8

As the deep learning revolution marches on, self-supervised learning has garnered increasing attention in recent years thanks to its remarkable representation learning ability and…

cs.CV2022★ 4 cited

OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning

Siyuan Li, Zedong Wang, Zicheng Liu +5

Mixup augmentation has emerged as a widely used technique for improving the generalization ability of deep neural networks (DNNs). However, the lack of standardized implementations…