6 citations · 7 across the 5 of their papers we have counts for
7 papers
TartanMatch: Towards Universal Dense Correspondence Across Modalities
Hyeokjoon Kwon, Jiting Cai, Ruogu Li +7
Robotic platforms combine multi-modal sensors to operate across diverse conditions, but most dense correspondence methods are limited to RGB-RGB or a small set of modality pairs. T…
Any4D: Unified Feed-Forward Metric 4D Reconstruction
Jay Karhade, Nikhil Keetha, Yuchen Zhang +4
We present Any4D, a scalable multi-view transformer for metric-scale, dense feed-forward 4D reconstruction. Any4D directly generates per-pixel motion and geometry predictions for N…
Unified Spherical Frontend: Learning Rotation-Equivariant Representations of Spherical Images from Any Camera
Mukai Yu, Mosam Dabhi, Liuyue Xie +2
Modern perception increasingly relies on fisheye, panoramic, and other wide field-of-view (FoV) cameras, yet most pipelines still apply planar CNNs designed for pinhole imagery on…
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Nikhil Keetha, Norman Müller, Johannes Schönberger +14
We introduce MapAnything, a unified transformer-based feed-forward model that ingests one or more images along with optional geometric inputs such as camera intrinsics, poses, dept…
UFM: A Simple Path towards Unified Dense Correspondence with Flow
Yuchen Zhang, Nikhil Keetha, Chenwei Lyu +9
Dense image correspondence is central to many applications, such as visual odometry, 3D reconstruction, object association, and re-identification. Historically, dense correspondenc…
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM
Nikhil Keetha, Jay Karhade, Krishna Murthy Jatavallabhula +4
Dense simultaneous localization and mapping (SLAM) is crucial for robotics and augmented reality applications. However, current methods are often hampered by the non-volumetric or…
2D-3D Pose Tracking with Multi-View Constraints
Huai Yu, Kuangyi Chen, Wen Yang +2
Camera localization in 3D LiDAR maps has gained increasing attention due to its promising ability to handle complex scenarios, surpassing the limitations of visual-only localizatio…