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 foundation model for zero-shot metric monocular depth estimation. Our model,
Depth Pro, synthesizes high-resolution depth maps with unparalleled sharpness and high …

Despite significant advancements in monocular depth estimation for static images,
estimating video depth in the open world remains challenging, since open-world videos are …

Most state-of-the-art point trackers are trained on synthetic data due to the difficulty of
annotating real videos for this task. However, this can result in suboptimal performance due …

Dynamic stereo matching is the task of estimating consistent disparities from stereo videos
with dynamic objects. Recent learning-based methods prioritize optimal performance on a …

Stereo matching provides depth estimation from binocular images for downstream
applications. These applications mostly take video streams as input and require temporally …

Stereo matching is close to hitting a half-century of history, yet witnessed a rapid evolution in
the last decade thanks to deep learning. While previous surveys in the late 2010s covered …

Video depth estimation has long been hindered by the scarcity of consistent and scalable
ground truth data, leading to inconsistent and unreliable results. In this paper, we introduce …

The recent advances in multimedia technology have significantly expanded the range of
audio-visual applications. The continuous enhancement of display quality has led to the …

With the rapid development of 3D reconstruction, especially the emergence of algorithms
such as NeRF and 3DGS, 3D reconstruction has become a popular research topic in recent …