5 citations · 7 across the 23 of their papers we have counts for
24 papers
GeoFace: Consistent Multi-View Face Generation with Geometry-Constrained Diffusion
Yeji Choi, Jinhyeok Choi, Jaewon Min +3
We present GeoFace, a geometry-constrained multi-view diffusion framework for consistent face generation from a single input. % While recent multi-view diffusion models achieve pho…
Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction
Jin Hyeon Kim, Jaeeun Lee, Claire Kim +8
Multi-view 3D reconstruction has achieved remarkable progress with the advent of feed-forward 3D reconstruction models. However, these models are typically trained and evaluated un…
Looped Diffusion Language Models
Sanghyun Lee, Chunsan Hong, Seungryong Kim +3
Masked diffusion models (MDMs) have emerged as a promising alternative to autoregressive models for language modeling, yet the effective design of transformer architectures for MDM…
WorldKV: Efficient World Memory with World Retrieval and Compression
Jung Yi, Minjae Kim, Paul Hyunbin Cho +3
Autoregressive video diffusion models have enabled real-time, action-conditioned world generation. However, sustaining a persistent world, where revisiting a previously seen viewpo…
Motion Cues from Image-based Point Tracking for LiDAR Scene Flow Estimation
Youngdong Jang, Gyeongrok Oh, Jong Wook Kim +6
LiDAR scene flow estimation is essential for autonomous driving, as it provides 3D motion for each point. Self-supervised approaches use static-dynamic classification to mitigate t…
Repurposing Geometric Foundation Models for Multi-view Diffusion
Wooseok Jang, Seonghu Jeon, Jisang Han +5
While recent advances in generative latent spaces have driven substantial progress in single-image generation, the optimal latent space for novel view synthesis (NVS) remains large…
WorldCam: Interactive Autoregressive 3D Gaming Worlds with Camera Pose as a Unifying Geometric Representation
Jisu Nam, Yicong Hong, Chun-Hao Paul Huang +9
Recent advances in video diffusion transformers have enabled interactive gaming world models that allow users to explore generated environments over extended horizons. However, exi…
Grounding World Simulation Models in a Real-World Metropolis
Junyoung Seo, Hyunwook Choi, Minkyung Kwon +10
What if a world simulation model could render not an imagined environment but a city that actually exists? Prior generative world models synthesize visually plausible yet artificia…
APPLE: Attribute-Preserving Pseudo-Labeling for Diffusion-Based Face Swapping
Jiwon Kang, Yeji Choi, JoungBin Lee +6
Face swapping aims to transfer the identity of a source face onto a target face while preserving target-specific attributes such as pose, expression, lighting, skin tone, and makeu…
V-Warper: Appearance-Consistent Video Diffusion Personalization via Value Warping
Hyunkoo Lee, Wooseok Jang, Jini Yang +4
Video personalization aims to generate videos that faithfully reflect a user-provided subject while following a text prompt. However, existing approaches often rely on heavy video-…
Lookahead Anchoring: Preserving Character Identity in Audio-Driven Human Animation
Junyoung Seo, Rodrigo Mira, Alexandros Haliassos +6
Audio-driven human animation models often suffer from identity drift during temporal autoregressive generation, where characters gradually lose their identity over time. One soluti…
TAG: Tangential Amplifying Guidance for Hallucination-Resistant Sampling
Hyunmin Cho, Donghoon Ahn, Susung Hong +3
Diffusion models achieve state-of-the-art image generation but often produce semantic inconsistencies, or hallucinations. Existing inference-time guidance methods rely on external…
Text-Aware Image Restoration with Diffusion Models
Jaewon Min, Jin Hyeon Kim, Paul Hyunbin Cho +6
Image restoration aims to recover degraded images. However, existing diffusion-based restoration methods, despite great success in natural image restoration, often struggle to fait…
Vid-CamEdit: Video Camera Trajectory Editing with Generative Rendering from Estimated Geometry
Junyoung Seo, Jisang Han, Jaewoo Jung +9
We introduce Vid-CamEdit, a novel framework for video camera trajectory editing, enabling the re-synthesis of monocular videos along user-defined camera paths. This task is challen…
Active Test-time Vision-Language Navigation
Heeju Ko, Sungjune Kim, Gyeongrok Oh +5
Vision-Language Navigation (VLN) policies trained on offline datasets often exhibit degraded task performance when deployed in unfamiliar navigation environments at test time, wher…
Where and How to Perturb: On the Design of Perturbation Guidance in Diffusion and Flow Models
Donghoon Ahn, Jiwon Kang, Sanghyun Lee +7
Recent guidance methods in diffusion models steer reverse sampling by perturbing the model to construct an implicit weak model and guide generation away from it. Among these approa…
A Noise is Worth Diffusion Guidance
Donghoon Ahn, Jiwon Kang, Sanghyun Lee +9
Diffusion models excel in generating high-quality images. However, current diffusion models struggle to produce reliable images without guidance methods, such as classifier-free gu…
ControlFace: Harnessing Facial Parametric Control for Face Rigging
Wooseok Jang, Youngjun Hong, Geonho Cha +1
Manipulation of facial images to meet specific controls such as pose, expression, and lighting, also known as face rigging, is a complex task in computer vision. Existing methods a…
Geometry-Aware Score Distillation via 3D Consistent Noising and Gradient Consistency Modeling
Min-Seop Kwak, Donghoon Ahn, Ines Hyeonsu Kim +2
Score distillation sampling (SDS), the methodology in which the score from pretrained 2D diffusion models is distilled into 3D representation, has recently brought significant adva…
Pose-dIVE: Pose-Diversified Augmentation with Diffusion Model for Person Re-Identification
Inès Hyeonsu Kim, Woojeong Jin, Soowon Son +6
Person re-identification (Re-ID) often faces challenges due to variations in human poses and camera viewpoints, which significantly affect the appearance of individuals across imag…
GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping
Junyoung Seo, Kazumi Fukuda, Takashi Shibuya +6
Generating novel views from a single image remains a challenging task due to the complexity of 3D scenes and the limited diversity in the existing multi-view datasets to train a mo…
Self-Rectifying Diffusion Sampling with Perturbed-Attention Guidance
Donghoon Ahn, Hyoungwon Cho, Jaewon Min +6
Recent studies have demonstrated that diffusion models are capable of generating high-quality samples, but their quality heavily depends on sampling guidance techniques, such as cl…
Retrieval-Augmented Score Distillation for Text-to-3D Generation
Junyoung Seo, Susung Hong, Wooseok Jang +4
Text-to-3D generation has achieved significant success by incorporating powerful 2D diffusion models, but insufficient 3D prior knowledge also leads to the inconsistency of 3D geom…
Debiasing Scores and Prompts of 2D Diffusion for View-consistent Text-to-3D Generation
Susung Hong, Donghoon Ahn, Seungryong Kim
Existing score-distilling text-to-3D generation techniques, despite their considerable promise, often encounter the view inconsistency problem. One of the most notable issues is th…