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TRAM: Global Trajectory and Motion of 3D Humans from in-the-wild Videos
We propose TRAM, a two-stage method to reconstruct a human's global trajectory and
motion from in-the-wild videos. TRAM robustifies SLAM to recover the camera motion in the …
motion from in-the-wild videos. TRAM robustifies SLAM to recover the camera motion in the …
From an Image to a Scene: Learning to Imagine the World from a Million 360° Videos
Abstract Three-dimensional (3D) understanding of objects and scenes play a key role in
humans' ability to interact with the world and has been an active area of research in …
humans' ability to interact with the world and has been an active area of research in …
Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos
We present a system that allows for accurate, fast, and robust estimation of camera
parameters and depth maps from casual monocular videos of dynamic scenes. Most …
parameters and depth maps from casual monocular videos of dynamic scenes. Most …
Graph-Guided Scene Reconstruction from Images with 3D Gaussian Splatting
This paper investigates an open research challenge of reconstructing high-quality, large 3D
open scenes from images. It is observed existing methods have various limitations, such as …
open scenes from images. It is observed existing methods have various limitations, such as …
MASt3R-SfM: a Fully-Integrated Solution for Unconstrained Structure-from-Motion
Structure-from-Motion (SfM), a task aiming at jointly recovering camera poses and 3D
geometry of a scene given a set of images, remains a hard problem with still many open …
geometry of a scene given a set of images, remains a hard problem with still many open …
Stereo4D: Learning How Things Move in 3D from Internet Stereo Videos
Learning to understand dynamic 3D scenes from imagery is crucial for applications ranging
from robotics to scene reconstruction. Yet, unlike other problems where large-scale …
from robotics to scene reconstruction. Yet, unlike other problems where large-scale …
Feat2GS: Probing Visual Foundation Models with Gaussian Splatting
Given that visual foundation models (VFMs) are trained on extensive datasets but often
limited to 2D images, a natural question arises: how well do they understand the 3D world …
limited to 2D images, a natural question arises: how well do they understand the 3D world …
Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation
Reconstructing the geometry and appearance of objects from photographs taken in different
environments is difficult as the illumination and therefore the object appearance vary across …
environments is difficult as the illumination and therefore the object appearance vary across …
D2S: Representing sparse descriptors and 3D coordinates for camera relocalization
State-of-the-art visual localization methods mostly rely on complex procedures to match
local descriptors and 3D point clouds. However, these procedures can incur significant costs …
local descriptors and 3D point clouds. However, these procedures can incur significant costs …
Exploring Matching Rates: From Keypoint Selection to Camera Relocalization
Camera relocalization is a challenging task to estimate camera pose within a known scene,
with wide applications in the fields of Virtual Reality (VR), Augmented Reality (AR), robotics …
with wide applications in the fields of Virtual Reality (VR), Augmented Reality (AR), robotics …