4 citations · 6 across the 4 of their papers we have counts for
7 papers · 1 filter
MV-RoMa: From Pairwise Matching into Multi-View Track Reconstruction
Jongmin Lee, Seungyeop Kang, Sungjoo Yoo
Establishing consistent correspondences across images is essential for 3D vision tasks such as structure-from-motion (SfM), yet most existing matchers operate in a pairwise manner,…
3D Equivariant Pose Regression via Direct Wigner-D Harmonics Prediction
Jongmin Lee, Minsu Cho
Determining the 3D orientations of an object in an image, known as single-image pose estimation, is a crucial task in 3D vision applications. Existing methods typically learn 3D ro…
Self-Supervised Equivariant Learning for Oriented Keypoint Detection
Jongmin Lee, Byungjin Kim, Minsu Cho
Detecting robust keypoints from an image is an integral part of many computer vision problems, and the characteristic orientation and scale of keypoints play an important role for…
Learning to Compose Hypercolumns for Visual Correspondence
Juhong Min, Jongmin Lee, Jean Ponce +1
Feature representation plays a crucial role in visual correspondence, and recent methods for image matching resort to deeply stacked convolutional layers. These models, however, ar…
SPair-71k: A Large-scale Benchmark for Semantic Correspondence
Juhong Min, Jongmin Lee, Jean Ponce +1
Establishing visual correspondences under large intra-class variations, which is often referred to as semantic correspondence or semantic matching, remains a challenging problem in…
Hyperpixel Flow: Semantic Correspondence with Multi-layer Neural Features
Juhong Min, Jongmin Lee, Jean Ponce +1
Establishing visual correspondences under large intra-class variations requires analyzing images at different levels, from features linked to semantics and context to local pattern…