Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …

Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

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 …

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 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 unified formulation and model for three motion and 3D perception tasks:
optical flow, rectified stereo matching and unrectified stereo depth estimation from posed …

Abstract The Cell Tracking Challenge is an ongoing benchmarking initiative that has
become a reference in cell segmentation and tracking algorithm development. Here, we …

Denoising diffusion probabilistic models have transformed image generation with their
impressive fidelity and diversity. We show that they also excel in estimating optical flow and …

We introduce optical Flow transFormer, dubbed as FlowFormer, a transformer-based neural
network architecture for learning optical flow. FlowFormer tokenizes the 4D cost volume built …