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20232026
most citedText2Control3D: Controllable 3D Avatar Generation in Neural Radiance Fields using Geometry-Guided Text-to-Image Diffusion Model

2 citations · 3 across the 17 of their papers we have counts for

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6 papers · 1 filter

cs.CV2025

Infinite-Homography as Robust Conditioning for Camera-Controlled Video Generation

Min-Jung Kim, Jeongho Kim, Hoiyeong Jin +2

Recent progress in video diffusion models has spurred growing interest in camera-controlled novel-view video generation for dynamic scenes, aiming to provide creators with cinemati…

cs.CV2025

EgoX: Egocentric Video Generation from a Single Exocentric Video

Taewoong Kang, Kinam Kim, Dohyeon Kim +3

Egocentric perception enables humans to experience and understand the world directly from their own point of view. Translating exocentric (third-person) videos into egocentric (fir…

cs.CV2025

InsertAnywhere: Geometrically Grounded and Optics-Aware Video Object Insertion

Hoiyeong Jin, Hyojin Jang, Junha Hyung +6

Recent advances in diffusion models have enabled impressive video editing capabilities, yet production-grade Video Object Insertion (VOI) remains challenging due to inadequate 4D s…

cs.RO2025

ACG: Action Coherence Guidance for Flow-based Vision-Language-Action models

Minho Park, Kinam Kim, Junha Hyung +5

Diffusion and flow matching models have emerged as powerful robot policies, enabling Vision-Language-Action (VLA) models to generalize across diverse scenes and instructions. Yet,…

cs.CL2025

Reward-Weighted Sampling: Enhancing Non-Autoregressive Characteristics in Masked Diffusion LLMs

Daehoon Gwak, Minseo Jung, Junwoo Park +4

Masked diffusion models (MDMs) offer a promising non-autoregressive alternative for large language modeling. Standard decoding methods for MDMs, such as confidence-based sampling,…

cs.CV2025

Temporal In-Context Fine-Tuning with Temporal Reasoning for Versatile Control of Video Diffusion Models

Kinam Kim, Junha Hyung, Jaegul Choo

Recent advances in text-to-video diffusion models have enabled high-quality video synthesis, but controllable generation remains challenging, particularly under limited data and co…