6 papers · 1 filter
3D-Aware Instance Segmentation and Tracking in Egocentric Videos
Yash Bhalgat, Vadim Tschernezki, Iro Laina +3
Egocentric videos present unique challenges for 3D scene understanding due to rapid camera motion, frequent object occlusions, and limited object visibility. This paper introduces…
CoTracker: It is Better to Track Together
Nikita Karaev, Ignacio Rocco, Benjamin Graham +3
We introduce CoTracker, a transformer-based model that tracks a large number of 2D points in long video sequences. Differently from most existing approaches that track points indep…
Diffusion Models for Open-Vocabulary Segmentation
Laurynas Karazija, Iro Laina, Andrea Vedaldi +1
Open-vocabulary segmentation is the task of segmenting anything that can be named in an image. Recently, large-scale vision-language modelling has led to significant advances in op…
N2F2: Hierarchical Scene Understanding with Nested Neural Feature Fields
Yash Bhalgat, Iro Laina, João F. Henriques +2
Understanding complex scenes at multiple levels of abstraction remains a formidable challenge in computer vision. To address this, we introduce Nested Neural Feature Fields (N2F2),…
Farm3D: Learning Articulated 3D Animals by Distilling 2D Diffusion
Tomas Jakab, Ruining Li, Shangzhe Wu +2
We present Farm3D, a method for learning category-specific 3D reconstructors for articulated objects, relying solely on "free" virtual supervision from a pre-trained 2D diffusion-b…
Splatter Image: Ultra-Fast Single-View 3D Reconstruction
Stanislaw Szymanowicz, Christian Rupprecht, Andrea Vedaldi
We introduce the \method, an ultra-efficient approach for monocular 3D object reconstruction. Splatter Image is based on Gaussian Splatting, which allows fast and high-quality reco…