activity
20152026
most citedLION: Latent Point Diffusion Models for 3D Shape Generation

190 citations · 998 across the 71 of their papers we have counts for

collaborators
Showing 2023Show all

10 papers · 1 filter

cs.CV2023

Dynamic LiDAR Re-simulation using Compositional Neural Fields

Hanfeng Wu, Xingxing Zuo, Stefan Leutenegger +3

We introduce DyNFL, a novel neural field-based approach for high-fidelity re-simulation of LiDAR scans in dynamic driving scenes. DyNFL processes LiDAR measurements from dynamic en…

cs.CV2023★ 1 cited

3DiffTection: 3D Object Detection with Geometry-Aware Diffusion Features

Chenfeng Xu, Huan Ling, Sanja Fidler +1

We present 3DiffTection, a state-of-the-art method for 3D object detection from single images, leveraging features from a 3D-aware diffusion model. Annotating large-scale image dat…

cs.CV2023★ 18 cited

EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision

Jiawei Yang, Boris Ivanovic, Or Litany +8

We present EmerNeRF, a simple yet powerful approach for learning spatial-temporal representations of dynamic driving scenes. Grounded in neural fields, EmerNeRF simultaneously capt…

cs.CV2023

Towards Viewpoint Robustness in Bird's Eye View Segmentation

Tzofi Klinghoffer, Jonah Philion, Wenzheng Chen +6

Autonomous vehicles (AV) require that neural networks used for perception be robust to different viewpoints if they are to be deployed across many types of vehicles without the rep…

cs.CV2023★ 6 cited

Semi-Supervised Semantic Segmentation via Marginal Contextual Information

Moshe Kimhi, Shai Kimhi, Evgenii Zheltonozhskii +2

We present a novel confidence refinement scheme that enhances pseudo labels in semi-supervised semantic segmentation. Unlike existing methods, which filter pixels with low-confiden…

cs.CV2023

Neural Kernel Surface Reconstruction

Jiahui Huang, Zan Gojcic, Matan Atzmon +3

We present a novel method for reconstructing a 3D implicit surface from a large-scale, sparse, and noisy point cloud. Our approach builds upon the recently introduced Neural Kernel…

cs.CV2023★ 1 cited

Fast Monocular Scene Reconstruction with Global-Sparse Local-Dense Grids

Wei Dong, Chris Choy, Charles Loop +3

Indoor scene reconstruction from monocular images has long been sought after by augmented reality and robotics developers. Recent advances in neural field representations and monoc…

cs.CV2023★ 3 cited

Neural LiDAR Fields for Novel View Synthesis

Shengyu Huang, Zan Gojcic, Zian Wang +5

We present Neural Fields for LiDAR (NFL), a method to optimise a neural field scene representation from LiDAR measurements, with the goal of synthesizing realistic LiDAR scans from…

cs.CV2023★ 1 cited

Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

Davis Rempe, Zhengyi Luo, Xue Bin Peng +5

We introduce a method for generating realistic pedestrian trajectories and full-body animations that can be controlled to meet user-defined goals. We draw on recent advances in gui…

cs.CV2023★ 1 cited

UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes

David Rozenberszki, Or Litany, Angela Dai

3D instance segmentation is fundamental to geometric understanding of the world around us. Existing methods for instance segmentation of 3D scenes rely on supervision from expensiv…