arXiv Computer Vision September 10, 2026 By Chenyue Cai, Anita Hu, James Lucas, Szymon Rusinkiewicz, Masha Shugrina

GLOSS: Geometric Local Self-Similarity Learning for Faithful Reference-Guided Texture Fill

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benchmarks

arXiv Computer Vision

Sep 1

OrnaStyler: Ornament-Aware Latent Editing for Content-Preserving 3D Stylization

arXiv:2608.29905v1 Announce Type: new Abstract: Text-guided style editing of 3D assets is essential for adapting existing objects to diverse visual aesthetics in digital content creation. Despite rap...

By Tomohiro Aizawa, Shigeru Kuriyama, Chunzhi Gu

benchmarks

arXiv AI

Jun 8

Native3D: End-to-End 3D Scene Generation via Unified Mesh-Texture Modeling and Semantic Alignment

arXiv:2606. 07117v1 Announce Type: cross Abstract: This paper presents Native3D, the first end-to-end 3D scene generation framework that completely bypasses 2D intermediate representations.

By Yibo Liu, Ziwei Zhang, Haozhou Pang, Menghao Li, Lanshan He, Gan Qi

llms diffusion fine-tuning safety

Hugging Face Trending Papers

Aug 10

SI-Edit: Toward Sketch-Instruction Guided Local Image Editing with Pixel-Level Precision

Despite rapid advances in generative models, achieving pixel-level precision in sketch-based image editing remains a persistent challenge, particularly for fine-grained local deformations. This gap stems primarily from the critical shortage of high-quality, publicly available benchmark datasets that jointly provide geometric constraints and semantic instructions.

llms multimodal benchmarks safety

arXiv AI

Jun 4

SAM 3D: 3Dfy Anything in Images

arXiv:2511. 16624v2 Announce Type: replace-cross Abstract: We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single image.

By SAM 3D Team, Xingyu Chen, Fu-Jen Chu, Pierre Gleize, Kevin J Liang, Alexander Sax, Hao Tang, Weiyao Wang, Michelle Guo, Thibaut Hardin, Xiang Li, Aohan Lin, Jiawei Liu, Ziqi Ma, Anushka Sagar, Bowen Song, Xiaodong Wang, Jianing Yang, Bowen Zhang, Piotr Doll\'ar, Georgia Gkioxari, Matt Feiszli, Jitendra Malik

benchmarks safety

arXiv Computer Vision

Sep 10

Guiding Image-to-3D Generation with Test-Time Partial Observations

arXiv:2609.10531v1 Announce Type: new Abstract: Image-to-3D models can generate visually compelling 3D assets from a single RGB image, but their geometry is often only loosely constrained by the avai...

By Jerred Chen, Simon Weber, Ronald Clark

fine-tuning

Hugging Face Trending Papers

Jul 14

DiTailed: Ensuring Visual Object Consistency in Text-Image-to-Image Flow Matching Models

Despite remarkable progress in text-guided image editing, generative models frequently fail to preserve visual object consistency, defined as the preservation of a subject's key attributes throughout the editing process. We address this limitation through three contributions.

rag diffusion