1 citations · 2 across the 7 of their papers we have counts for
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TAPNext++: What's Next for Tracking Any Point (TAP)?
Sebastian Jung, Artem Zholus, Martin Sundermeyer +6
Tracking-Any-Point (TAP) models aim to track any point through a video which is a crucial task in AR/XR and robotics applications. The recently introduced TAPNext approach proposes…
RiemanLine: Riemannian Manifold Representation of 3D Lines for Factor Graph Optimization
Yan Li, Ze Yang, Keisuke Tateno +3
Minimal parametrization of 3D lines plays a critical role in camera localization and structural mapping. Existing representations in robotics and computer vision predominantly hand…
4D Gaussian Splatting SLAM
Yanyan Li, Youxu Fang, Zunjie Zhu +3
Simultaneously localizing camera poses and constructing Gaussian radiance fields in dynamic scenes establish a crucial bridge between 2D images and the 4D real world. Instead of re…
SmileSplat: Generalizable Gaussian Splats for Unconstrained Sparse Images
Yanyan Li, Yixin Fang, Federico Tombari +1
Sparse Multi-view Images can be Learned to predict explicit radiance fields via Generalizable Gaussian Splatting approaches, which can achieve wider application prospects in real-l…
GeoGaussian: Geometry-aware Gaussian Splatting for Scene Rendering
Yanyan Li, Chenyu Lyu, Yan Di +3
During the Gaussian Splatting optimization process, the scene's geometry can gradually deteriorate if its structure is not deliberately preserved, especially in non-textured region…
E-Graph: Minimal Solution for Rigid Rotation with Extensibility Graphs
Yanyan Li, Federico Tombari
Minimal solutions for relative rotation and translation estimation tasks have been explored in different scenarios, typically relying on the so-called co-visibility graph. However,…