activity
20222026
most citedADAS: A Direct Adaptation Strategy for Multi-Target Domain Adaptive Semantic Segmentation

2 citations · 5 across the 13 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CV2025

Scale-invariant and View-relational Representation Learning for Full Surround Monocular Depth

Kyumin Hwang, Wonhyeok Choi, Kiljoon Han +5

Recent foundation models demonstrate strong generalization capabilities in monocular depth estimation. However, directly applying these models to Full Surround Monocular Depth Esti…

cs.CV2025

Infinite-Story: A Training-Free Consistent Text-to-Image Generation

Jihun Park, Kyoungmin Lee, Jongmin Gim +7

We present Infinite-Story, a training-free framework for consistent text-to-image (T2I) generation tailored for multi-prompt storytelling scenarios. Built upon a scale-wise autoreg…

cs.LG2025

Prompt-Based Safety Guidance Is Ineffective for Unlearned Text-to-Image Diffusion Models

Jiwoo Shin, Byeonghu Na, Mina Kang +2

Recent advances in text-to-image generative models have raised concerns about their potential to produce harmful content when provided with malicious input text prompts. To address…

cs.CV2025

Temporal Grounding as a Learning Signal for Referring Video Object Segmentation

Seunghun Lee, Jiwan Seo, Jeonghoon Kim +9

Referring Video Object Segmentation (RVOS) aims to segment and track objects in videos based on natural language expressions, requiring precise alignment between visual content and…

cs.CV2025

A Training-Free Style-Personalization via SVD-Based Feature Decomposition

Kyoungmin Lee, Jihun Park, Jongmin Gim +4

We present a training-free framework for style-personalized image generation that operates during inference using a scale-wise autoregressive model. Our method generates a stylized…

cs.CV2025

Intrinsic Image Decomposition for Robust Self-supervised Monocular Depth Estimation on Reflective Surfaces

Wonhyeok Choi, Kyumin Hwang, Minwoo Choi +4

Self-supervised monocular depth estimation (SSMDE) has gained attention in the field of deep learning as it estimates depth without requiring ground truth depth maps. This approach…

cs.CV2025

Self-supervised Monocular Depth Estimation Robust to Reflective Surface Leveraged by Triplet Mining

Wonhyeok Choi, Kyumin Hwang, Wei Peng +2

Self-supervised monocular depth estimation (SSMDE) aims to predict the dense depth map of a monocular image, by learning depth from RGB image sequences, eliminating the need for gr…