Search Results for author:
Found 8 papers, 2 papers with code
ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting
We present ODE-GS, a novel method that unifies 3D Gaussian Splatting with latent neural ordinary differential equations (ODEs) to forecast dynamic 3D scenes far beyond the time span seen during training.
Radar-Guided Polynomial Fitting for Metric Depth Estimation
We propose PolyRad, a novel radar-guided depth estimation method that introduces polynomial fitting to transform scaleless depth predictions from pretrained monocular depth estimation (MDE) models into metric depth maps.
ProtoDepth: Unsupervised Continual Depth Completion with Prototypes
To extend ProtoDepth to the challenging setting where the test-time domain identity is withheld, we propose to learn domain descriptors that enable the model to select the appropriate prototype set for inference.
PriorDiffusion: Leverage Language Prior in Diffusion Models for Monocular Depth Estimation
We argue that language prior can enhance monocular depth estimation by leveraging the inductive bias learned during the text-to-image pre-training of diffusion models.
UnCLe: Unsupervised Continual Learning of Depth Completion
We find that unsupervised continual learning of depth completion is an open problem, and we invite researchers to leverage UnCLe as a development platform.
SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection
However, given that objects occupy only a small part of a scene, finding dense candidates and generating dense representations is noisy and inefficient.
Quadric Representations for LiDAR Odometry, Mapping and Localization
Current LiDAR odometry, mapping and localization methods leverage point-wise representations of 3D scenes and achieve high accuracy in autonomous driving tasks.
Validating Planck SZ2 Clusters with Optical Counterparts
We perform an extensive analysis of optical counterparts of Planck PSZ2 clusters, considering matches with three recent catalogs built from SDSS data: AMF DR9, redMaPPer (v6. 3) and Wen et al (WHL).
Cosmology and Nongalactic Astrophysics
