2 citations · 2 across the 6 of their papers we have counts for
7 papers
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…
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…
Latest Object Memory Management for Temporally Consistent Video Instance Segmentation
Seunghun Lee, Jiwan Seo, Minwoo Choi +6
In this paper, we present Latest Object Memory Management (LOMM) for temporally consistent video instance segmentation that significantly improves long-term instance tracking. At t…
A Training-Free Style-aligned Image Generation with Scale-wise Autoregressive Model
Jihun Park, Jongmin Gim, Kyoungmin Lee +5
We present a training-free style-aligned image generation method that leverages a scale-wise autoregressive model. While large-scale text-to-image (T2I) models, particularly diffus…
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…
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…