arXiv Computer Vision
Segmentation of Moving Objects During Camera Motion Using the OWL Function
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Related stories
arXiv Computer Vision
Sep 30
Moving Object Detection from Moving Camera Using Focus of Expansion Likelihood and Segmentation
arXiv:2507.13628v3 Announce Type: replace Abstract: Separating moving and static objects from a moving camera viewpoint is essential for 3D reconstruction, autonomous navigation, and scene understand...
Hugging Face Trending Papers
Jun 1
TROPHIES: Temporal Reconstruction of Places, Humans, and Cameras from Multi-view Videos
Reconstructing humans and their surrounding environments in a globally consistent 4D space is essential for comprehensive perception. However, prior works typically assume single-view inputs or decouple humans, scenes, and cameras, making them unable to recover coherent geometry, stable motion, and physically aligned trajectories.
arXiv Computer Vision
Oct 15
Object Pose from 2-D to 3-D Point and Line Correspondences
arXiv:2610.19734v1 Announce Type: new Abstract: In this paper we present a method for optimally estimating the rotation and translation between a camera and a 3-D object from point and/or line corres...
arXiv Computer Vision
Sep 15
Multi-View Structure-from-Motion Enables Oriented Projective Shape Analysis in Three Dimensions
arXiv:2609.13263v1 Announce Type: new Abstract: Projective shape analysis provides a geometric framework for studying landmark configurations in digital images acquired by pinhole cameras. In the cla...
arXiv Computer Vision
Oct 21
HRoPE: Homography Relative Positional Encoding
arXiv:2610.28284v1 Announce Type: new Abstract: Geometric Relative Positional Encoding has become the primary mechanism for injecting spatial inductive biases into multi-view transformers. Existing d...
arXiv Computer Vision
Sep 2
CQF-HMR: Continuous Quaternion Flows for Probabilistic 3D Human Mesh Recovery from a Single Image
arXiv:2609.00995v1 Announce Type: new Abstract: Recovering 3D digital humans from a single 2D image is an ill-posed computer vision problem due to the loss of depth information. Probabilistic 3D huma...