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Found 7 papers, 1 papers with code
S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations
Following the tracking-by-attention paradigm, this paper introduces an object-centric, transformer-based framework for tracking in 3D.
Semantic Scene Completion using Local Deep Implicit Functions on LiDAR Data
We show that this continuous representation is suitable to encode geometric and semantic properties of extensive outdoor scenes without the need for spatial discretization (thus avoiding the trade-off between level of scene detail and the scene extent that can be covered).
Ranked #5 on
3D Semantic Scene Completion
on SemanticKITTI
CNN-based synthesis of realistic high-resolution LiDAR data
This paper presents a novel CNN-based approach for synthesizing high-resolution LiDAR point cloud data.
Improved Semantic Stixels via Multimodal Sensor Fusion
Our results indicate that the proposed mid-level fusion of LiDAR and camera data improves both the geometric and semantic accuracy of the Stixel model significantly while reducing the computational overhead as well as the amount of generated data in comparison to using a single modality on its own.
Boosting LiDAR-based Semantic Labeling by Cross-Modal Training Data Generation
The effectiveness of the proposed network architecture as well as the automated data generation process is demonstrated on a manually annotated ground truth dataset.
The Stixel world: A medium-level representation of traffic scenes
We believe this challenge should be faced by introducing a representation of the sensory data that provides compressed and structured access to all relevant visual content of the scene.
The Cityscapes Dataset for Semantic Urban Scene Understanding
Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications.
