10 citations · 11 across the 7 of their papers we have counts for
7 papers
KFD-NeRF: Rethinking Dynamic NeRF with Kalman Filter
Yifan Zhan, Zhuoxiao Li, Muyao Niu +4
We introduce KFD-NeRF, a novel dynamic neural radiance field integrated with an efficient and high-quality motion reconstruction framework based on Kalman filtering. Our key idea i…
DeepShaRM: Multi-View Shape and Reflectance Map Recovery Under Unknown Lighting
Kohei Yamashita, Shohei Nobuhara, Ko Nishino
Geometry reconstruction of textureless, non-Lambertian objects under unknown natural illumination (i.e., in the wild) remains challenging as correspondences cannot be established a…
TransPoser: Transformer as an Optimizer for Joint Object Shape and Pose Estimation
Yuta Yoshitake, Mai Nishimura, Shohei Nobuhara +1
We propose a novel method for joint estimation of shape and pose of rigid objects from their sequentially observed RGB-D images. In sharp contrast to past approaches that rely on c…
InCrowdFormer: On-Ground Pedestrian World Model From Egocentric Views
Mai Nishimura, Shohei Nobuhara, Ko Nishino
We introduce an on-ground Pedestrian World Model, a computational model that can predict how pedestrians move around an observer in the crowd on the ground plane, but from just the…
BlindSpotNet: Seeing Where We Cannot See
Taichi Fukuda, Kotaro Hasegawa, Shinya Ishizaki +2
We introduce 2D blind spot estimation as a critical visual task for road scene understanding. By automatically detecting road regions that are occluded from the vehicle's vantage p…
nLMVS-Net: Deep Non-Lambertian Multi-View Stereo
Kohei Yamashita, Yuto Enyo, Shohei Nobuhara +1
We introduce a novel multi-view stereo (MVS) method that can simultaneously recover not just per-pixel depth but also surface normals, together with the reflectance of textureless,…