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20232026
most citedPosterior Distillation Sampling

2 citations · 2 across the 12 of their papers we have counts for

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9 papers · 1 filter

cs.CV2026

Retrieval Heads Meet Vision: Uncovering How VLMs Locate and Extract Visual Information

Chanho Park, Daehyeon Choi, Jihyun Lee +1

Vision-language models (VLMs) can locate an image region referred to by a text prompt and route the corresponding visual evidence to the output, yet the internal mechanism behind t…

cs.CV2025

MatLat: Material Latent Space for PBR Texture Generation

Kyeongmin Yeo, Yunhong Min, Jaihoon Kim +1

We propose a generative framework for producing high-quality PBR textures on a given 3D mesh. As large-scale PBR texture datasets are scarce, our approach focuses on effectively le…

cs.CV2025

Toward Ambulatory Vision: Learning Visually-Grounded Active View Selection

Juil Koo, Daehyeon Choi, Sangwoo Youn +2

Vision Language Models (VLMs) excel at visual question answering (VQA) but remain limited to snapshot vision, reasoning from static images. In contrast, embodied agents require amb…

cs.CV2025

VideoHandles: Editing 3D Object Compositions in Videos Using Video Generative Priors

Juil Koo, Paul Guerrero, Chun-Hao Paul Huang +2

Generative methods for image and video editing use generative models as priors to perform edits despite incomplete information, such as changing the composition of 3D objects shown…

cs.CV2025

StochSync: Stochastic Diffusion Synchronization for Image Generation in Arbitrary Spaces

Kyeongmin Yeo, Jaihoon Kim, Minhyuk Sung

We propose a zero-shot method for generating images in arbitrary spaces (e.g., a sphere for 360° panoramas and a mesh surface for texture) using a pretrained image diffusion model.…

cs.CV2025

ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generation

Yunhong Min, Daehyeon Choi, Kyeongmin Yeo +2

We introduce ORIGEN, the first zero-shot method for 3D orientation grounding in text-to-image generation across multiple objects and diverse categories. While previous work on spat…

cs.CV2024

Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses

Seungwoo Yoo, Juil Koo, Kyeongmin Yeo +1

We propose a novel method for learning representations of poses for 3D deformable objects, which specializes in 1) disentangling pose information from the object's identity, 2) fac…

cs.CV2024

SyncTweedies: A General Generative Framework Based on Synchronized Diffusions

Jaihoon Kim, Juil Koo, Kyeongmin Yeo +1

We introduce a general framework for generating diverse visual content, including ambiguous images, panorama images, mesh textures, and Gaussian splat textures, by synchronizing mu…

cs.CV2023★ 2 cited

Posterior Distillation Sampling

Juil Koo, Chanho Park, Minhyuk Sung

We introduce Posterior Distillation Sampling (PDS), a novel optimization method for parametric image editing based on diffusion models. Existing optimization-based methods, which l…