7 citations · 8 across the 14 of their papers we have counts for
15 papers
Puffin-World: Scaling a Unified Multimodal Model with Native 3D World States
Kang Liao, Yihang Luo, Xiao-Ming Wu +7
We propose Puffin-World, a unified multimodal architecture that integrates physical understanding, spatial simulation, and 3D world generation and reconstruction without relying on…
ORBIT++: Benchmarking SfM in the Wild with 360° Video
Sara Sabour, Linyi Jin, Richard Tucker +9
Structure-from-Motion (SfM) is a cornerstone of 3D perception, yet current methods often fail when applied to complex videos involving challenging camera motions or dynamic scenes.…
Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation
Kang Liao, Size Wu, Zhonghua Wu +6
Camera-centric understanding and generation are two cornerstones of spatial intelligence, yet they are typically studied in isolation. We present Puffin, a unified camera-centric m…
Eye2Eye: A Simple Approach for Monocular-to-Stereo Video Synthesis
Michal Geyer, Omer Tov, Linyi Jin +4
The rising popularity of immersive visual experiences has increased interest in stereoscopic 3D video generation. Despite significant advances in video synthesis, creating 3D video…
MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos
Zhengqi Li, Richard Tucker, Forrester Cole +6
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 conventional stru…
Stereo4D: Learning How Things Move in 3D from Internet Stereo Videos
Linyi Jin, Richard Tucker, Zhengqi Li +3
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 superv…
3DFIRES: Few Image 3D REconstruction for Scenes with Hidden Surface
Linyi Jin, Nilesh Kulkarni, David Fouhey
This paper introduces 3DFIRES, a novel system for scene-level 3D reconstruction from posed images. Designed to work with as few as one view, 3DFIRES reconstructs the complete geome…
FAR: Flexible, Accurate and Robust 6DoF Relative Camera Pose Estimation
Chris Rockwell, Nilesh Kulkarni, Linyi Jin +3
Estimating relative camera poses between images has been a central problem in computer vision. Methods that find correspondences and solve for the fundamental matrix offer high pre…
Learning to Predict Scene-Level Implicit 3D from Posed RGBD Data
Nilesh Kulkarni, Linyi Jin, Justin Johnson +1
We introduce a method that can learn to predict scene-level implicit functions for 3D reconstruction from posed RGBD data. At test time, our system maps a previously unseen RGB ima…
Perspective Fields for Single Image Camera Calibration
Linyi Jin, Jianming Zhang, Yannick Hold-Geoffroy +4
Geometric camera calibration is often required for applications that understand the perspective of the image. We propose perspective fields as a representation that models the loca…
PlaneFormers: From Sparse View Planes to 3D Reconstruction
Samir Agarwala, Linyi Jin, Chris Rockwell +1
We present an approach for the planar surface reconstruction of a scene from images with limited overlap. This reconstruction task is challenging since it requires jointly reasonin…
Understanding 3D Object Articulation in Internet Videos
Shengyi Qian, Linyi Jin, Chris Rockwell +2
We propose to investigate detecting and characterizing the 3D planar articulation of objects from ordinary videos. While seemingly easy for humans, this problem poses many challeng…
Planar Surface Reconstruction from Sparse Views
Linyi Jin, Shengyi Qian, Andrew Owens +1
The paper studies planar surface reconstruction of indoor scenes from two views with unknown camera poses. While prior approaches have successfully created object-centric reconstru…
Associative3D: Volumetric Reconstruction from Sparse Views
Shengyi Qian, Linyi Jin, David F. Fouhey
This paper studies the problem of 3D volumetric reconstruction from two views of a scene with an unknown camera. While seemingly easy for humans, this problem poses many challenges…
Inferring Occluded Geometry Improves Performance when Retrieving an Object from Dense Clutter
Andrew Price, Linyi Jin, Dmitry Berenson
Object search -- the problem of finding a target object in a cluttered scene -- is essential to solve for many robotics applications in warehouse and household environments. Howeve…