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20152025
most citedMove to See Better: Self-Improving Embodied Object Detection

14 citations · 18 across the 4 of their papers we have counts for

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24 papers · 1 filter

cs.CV2025

PointSt3R: Point Tracking through 3D Grounded Correspondence

Rhodri Guerrier, Adam W. Harley, Dima Damen

Recent advances in foundational 3D reconstruction models, such as DUSt3R and MASt3R, have shown great potential in 2D and 3D correspondence in static scenes. In this paper, we prop…

cs.CV2025

Generative Point Tracking with Flow Matching

Mattie Tesfaldet, Adam W. Harley, Konstantinos G. Derpanis +2

Tracking a point through a video can be a challenging task due to uncertainty arising from visual obfuscations, such as appearance changes and occlusions. Although current state-of…

cs.CV2025

AllTracker: Efficient Dense Point Tracking at High Resolution

Adam W. Harley, Yang You, Xinglong Sun +11

We introduce AllTracker: a model that estimates long-range point tracks by way of estimating the flow field between a query frame and every other frame of a video. Unlike existing…

cs.CV2025

TAPIP3D: Tracking Any Point in Persistent 3D Geometry

Bowei Zhang, Lei Ke, Adam W. Harley +1

We introduce TAPIP3D, a novel approach for long-term 3D point tracking in monocular RGB and RGB-D videos. TAPIP3D represents videos as camera-stabilized spatio-temporal feature clo…

cs.CV2024

EgoPoints: Advancing Point Tracking for Egocentric Videos

Ahmad Darkhalil, Rhodri Guerrier, Adam W. Harley +1

We introduce EgoPoints, a benchmark for point tracking in egocentric videos. We annotate 4.7K challenging tracks in egocentric sequences. Compared to the popular TAP-Vid-DAVIS eval…

cs.CV2024

View-Consistent Hierarchical 3D Segmentation Using Ultrametric Feature Fields

Haodi He, Colton Stearns, Adam W. Harley +1

Large-scale vision foundation models such as Segment Anything (SAM) demonstrate impressive performance in zero-shot image segmentation at multiple levels of granularity. However, t…