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From the 1 of 12 linked papers with an AI index.

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20242026
most citedScaling Laws in Patchification: An Image Is Worth 50,176 Tokens And More

2 citations · 2 across the 2 of their papers we have counts for

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12 papers

cs.CV2026

Let RGB Be the Language of Vision

Timing Yang, Jinrui Yang, Xinlong Li +11

The paper proposes a unified vision framework that encodes all visual signals—including images, masks, and depth maps—as RGB images, turning diverse tasks into a common RGB-to-RGB…

cs.CV2026

RATS! Patches Talk Through Registers: Emergent Parts in Register Attention Transformers

Timing Yang, Predrag Neskovic, Jansen Seheult +4

When humans see a bird, they recognize far more than just "bird" -- they see a head, wings, and talons, a structured assembly of reusable parts that can be identified across every…

cs.CV20262 cited

Scaling Laws in Patchification: An Image Is Worth 50,176 Tokens And More

Feng Wang, Yaodong Yu, Guoyizhe Wei +4

Since the introduction of Vision Transformer (ViT), patchification has long been regarded as a de facto image tokenization approach for plain visual architectures. By compressing t…

cs.CV2026

ViT-5: Vision Transformers for The Mid-2020s

Feng Wang, Sucheng Ren, Tiezheng Zhang +4

This work presents a systematic investigation into modernizing Vision Transformer backbones by leveraging architectural advancements from the past five years. While preserving the…

cs.CV2026

WorldEdit: Towards Open-World Image Editing with a Knowledge-Informed Benchmark

Wang Lin, Feng Wang, Majun Zhang +7

Recent advances in image editing models have demonstrated remarkable capabilities in executing explicit instructions, such as attribute manipulation, style transfer, and pose synth…

cs.CV2025

ViMix-14M: A Curated Multi-Source Video-Text Dataset with Long-Form, High-Quality Captions and Crawl-Free Access

Timing Yang, Sucheng Ren, Alan Yuille +1

Text-to-video generation has surged in interest since Sora, yet open-source models still face a data bottleneck: there is no large, high-quality, easily obtainable video-text corpu…