We present a new test-time optimization method for estimating dense and long-range motion
from a video sequence. Prior optical flow or particle video tracking algorithms typically …

We introduce PointOdyssey, a large-scale synthetic dataset, and data generation framework,
for the training and evaluation of long-term fine-grained tracking algorithms. Our goal is to …

We present a method that simultaneously addresses the tasks of dynamic scene novel-view
synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We …

We present a novel model for Tracking Any Point (TAP) that effectively tracks any queried
point on any physical surface throughout a video sequence. Our approach employs two …

We present a method that simultaneously addresses the tasks of dynamic scene novel-view
synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We …

As computer vision algorithms increase in capability, their applications in clinical systems
will become more pervasive. These applications include: diagnostics, such as colonoscopy …

We introduce VideoFlow, a novel optical flow estimation framework for videos. In contrast to
previous methods that learn to estimate optical flow from two frames, VideoFlow concurrently …

In this paper we introduce Fairy a minimalist yet robust adaptation of image-editing diffusion
models enhancing them for video editing applications. Our approach centers on the concept …

We propose a novel multimodal video benchmark-the Perception Test-to evaluate the
perception and reasoning skills of pre-trained multimodal models (eg Flamingo, BEiT-3, or …

Current diffusion-based video editing primarily focuses on structure-preserved editing by
utilizing various dense correspondences to ensure temporal consistency and motion …