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20232026
most citedED-NeRF: Efficient Text-Guided Editing of 3D Scene with Latent Space NeRF

8 citations · 11 across the 14 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

GeoFix: Geometry Fixing for 4D Consistent Generation

Yeobin Hong, Hyojun Go, Dohun Lee +7

Video diffusion models increasingly serve as priors for 4D generation, but the generated videos often lack geometric consistency. Recent approaches address this through post-traini…

cs.LG2026

Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models

Jaa-Yeon Lee, Yeobin Hong, Taesung Kwon +1

Diffusion models generate highly realistic images but often struggle with precise text-image alignment. While recent post-training methods improve alignment using external rewards…

cs.LG2026

Aligning Few-Step Generative Models by Amortizing Sample-based Variational Inference

Jaewoo Lee, Hyeongyu Kang, Dohyun Kim +9

Aligning a few-step generative model is challenging, since existing alignment frameworks typically rely on restrictive assumptions: a tractable likelihood, a specific ODE/SDE solve…

cs.CV2026

MeshReGen: A Unified 3D Geometry Regeneration Framework

Geon Yeong Park, Roman Shapovalov, Rakesh Ranjan +3

We consider the problem of regenerating 3D objects from 2D images and initial 3D shapes. Most 3D generators operate in a one-shot fashion, converting text or images to a 3D object…

cs.CV2026

Memory-V2V: Memory-Augmented Video-to-Video Diffusion for Consistent Multi-Turn Editing

Dohun Lee, Chun-Hao Paul Huang, Xuelin Chen +3

Video-to-video diffusion models achieve impressive single-turn editing performance, but practical editing workflows are inherently iterative. When edits are applied sequentially, e…