13 citations · 45 across the 20 of their papers we have counts for
8 papers · 1 filter
Privacy-Preserving Visual Localization with Event Cameras
Junho Kim, Young Min Kim, Ramzi Zahreddine +4
We consider the problem of client-server localization, where edge device users communicate visual data with the service provider for locating oneself against a pre-built 3D map. Th…
MoDA: Map style transfer for self-supervised Domain Adaptation of embodied agents
Eun Sun Lee, Junho Kim, SangWon Park +1
We propose a domain adaptation method, MoDA, which adapts a pretrained embodied agent to a new, noisy environment without ground-truth supervision. Map-based memory provides import…
IBL-NeRF: Image-Based Lighting Formulation of Neural Radiance Fields
Changwoon Choi, Juhyeon Kim, Young Min Kim
We propose IBL-NeRF, which decomposes the neural radiance fields (NeRF) of large-scale indoor scenes into intrinsic components. Recent approaches further decompose the baked radian…
CPO: Change Robust Panorama to Point Cloud Localization
Junho Kim, Hojun Jang, Changwoon Choi +1
We present CPO, a fast and robust algorithm that localizes a 2D panorama with respect to a 3D point cloud of a scene possibly containing changes. To robustly handle scene changes,…
Ev-NeRF: Event Based Neural Radiance Field
Inwoo Hwang, Junho Kim, Young Min Kim
We present Ev-NeRF, a Neural Radiance Field derived from event data. While event cameras can measure subtle brightness changes in high frame rates, the measurements in low lighting…
Probabilistic Implicit Scene Completion
Dongsu Zhang, Changwoon Choi, Inbum Park +1
We propose a probabilistic shape completion method extended to the continuous geometry of large-scale 3D scenes. Real-world scans of 3D scenes suffer from a considerable amount of…
Ev-TTA: Test-Time Adaptation for Event-Based Object Recognition
Junho Kim, Inwoo Hwang, Young Min Kim
We introduce Ev-TTA, a simple, effective test-time adaptation algorithm for event-based object recognition. While event cameras are proposed to provide measurements of scenes with…
Neural Marionette: Unsupervised Learning of Motion Skeleton and Latent Dynamics from Volumetric Video
Jinseok Bae, Hojun Jang, Cheol-Hui Min +2
We present Neural Marionette, an unsupervised approach that discovers the skeletal structure from a dynamic sequence and learns to generate diverse motions that are consistent with…