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 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 …

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 …

Recovering dense and long-range pixel motion in videos is a challenging problem. Part of
the difficulty arises from the 3D-to-2D projection process leading to occlusions and …

We present DINO-Tracker–a new framework for long-term dense tracking in video. The pillar
of our approach is combining test-time training on a single video, with the powerful localized …

Recent approaches to point tracking are able to recover the trajectory of any scene point
through a large portion of a video despite the presence of occlusions. They are however too …

In this paper, we propose a simple yet effective approach for Tracking Any Point with
TRansformers (TAPTR). Based on the observation that point tracking bears a great …

In this paper, we present TAPTRv2, a Transformer-based approach built upon TAPTR for
solving the Tracking Any Point (TAP) task. TAPTR borrows designs from DEtection …

Video representation is a long-standing problem that is crucial for various downstream tasks,
such as tracking, depth prediction, segmentation, view synthesis, and editing. However …

We introduce LocoTrack, a highly accurate and efficient model designed for the task of
tracking any point (TAP) across video sequences. Previous approaches in this task often rely …