562 citations · 694 across the 9 of their papers we have counts for
10 papers · 1 filter
Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding
Chang Liu, Henghui Ding, Nikhila Ravi +40
This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…
FACET: Fairness in Computer Vision Evaluation Benchmark
Laura Gustafson, Chloe Rolland, Nikhila Ravi +5
Computer vision models have known performance disparities across attributes such as gender and skin tone. This means during tasks such as classification and detection, model perfor…
Segment Anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi +9
We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest seg…
Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild
Garrick Brazil, Abhinav Kumar, Julian Straub +3
Recognizing scenes and objects in 3D from a single image is a longstanding goal of computer vision with applications in robotics and AR/VR. For 2D recognition, large datasets and s…
Learning 3D Object Shape and Layout without 3D Supervision
Georgia Gkioxari, Nikhila Ravi, Justin Johnson
A 3D scene consists of a set of objects, each with a shape and a layout giving their position in space. Understanding 3D scenes from 2D images is an important goal, with applicatio…
Recognizing Scenes from Novel Viewpoints
Shengyi Qian, Alexander Kirillov, Nikhila Ravi +4
Humans can perceive scenes in 3D from a handful of 2D views. For AI agents, the ability to recognize a scene from any viewpoint given only a few images enables them to efficiently…
PyTorchVideo: A Deep Learning Library for Video Understanding
Haoqi Fan, Tullie Murrell, Heng Wang +13
We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tas…
Accelerating 3D Deep Learning with PyTorch3D
Nikhila Ravi, Jeremy Reizenstein, David Novotny +4
Deep learning has significantly improved 2D image recognition. Extending into 3D may advance many new applications including autonomous vehicles, virtual and augmented reality, aut…
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion
David Novotny, Nikhila Ravi, Benjamin Graham +2
We propose C3DPO, a method for extracting 3D models of deformable objects from 2D keypoint annotations in unconstrained images. We do so by learning a deep network that reconstruct…
New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-Resolution
Yijie Bei, Alex Damian, Shijia Hu +3
This work identifies and addresses two important technical challenges in single-image super-resolution: (1) how to upsample an image without magnifying noise and (2) how to preserv…