1 citations · 1 across the 5 of their papers we have counts for
6 papers
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…
LiLoc: Lifelong Localization using Adaptive Submap Joining and Egocentric Factor Graph
Yixin Fang, Yanyan Li, Kun Qian +3
This paper proposes a versatile graph-based lifelong localization framework, LiLoc, which enhances its timeliness by maintaining a single central session while improves the accurac…
Semantic Dense Reconstruction with Consistent Scene Segments
Yingcai Wan, Yanyan Li, Yingxuan You +3
In this paper, a method for dense semantic 3D scene reconstruction from an RGB-D sequence is proposed to solve high-level scene understanding tasks. First, each RGB-D pair is consi…