SST
Code for a series of work in LiDAR perception, including SST (CVPR 22), FSD (NeurIPS 22), FSD++ (TPAMI 23), FSDv2, and CTRL (ICCV 23, oral). (by tusen-ai)
Ultra-Fast-Lane-Detection
Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020) (by cfzd)
SST | Ultra-Fast-Lane-Detection | |
---|---|---|
1 | 1 | |
742 | 1,680 | |
2.3% | - | |
6.7 | 0.0 | |
7 months ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SST
Posts with mentions or reviews of SST.
We have used some of these posts to build our list of alternatives
and similar projects.
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Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection
This paper aims for high-performance offline LiDAR-based 3D object detection. We first observe that experienced human annotators annotate objects from a track-centric perspective. They first label the objects with clear shapes in a track, and then leverage the temporal coherence to infer the annotations of obscure objects. Drawing inspiration from this, we propose a high-performance offline detector in a track-centric perspective instead of the conventional object-centric perspective. Our method features a bidirectional tracking module and a track-centric learning module. Such a design allows our detector to infer and refine a complete track once the object is detected at a certain moment. We refer to this characteristic as "onCe detecTed, neveR Lost" and name the proposed system CTRL. Extensive experiments demonstrate the remarkable performance of our method, surpassing the human-level annotating accuracy and the previous state-of-the-art methods in the highly competitive Waymo Open Dataset without model ensemble. The code will be made publicly available at https://github.com/tusen-ai/SST.
Ultra-Fast-Lane-Detection
Posts with mentions or reviews of Ultra-Fast-Lane-Detection.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-23.
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Lane Assist system I've been working on over the past few days.
The way this works is that great minds made a paper about lane detection.
What are some alternatives?
When comparing SST and Ultra-Fast-Lane-Detection you can also consider the following projects:
Euro-Truck-Simulator-2-Lane-Assist - Plugin based interface program for ETS2/ATS.
PaddleSeg - Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.
Ultrafast-Lane-Detection-Inference-Pytorch- - Example scripts for the detection of lanes using the ultra fast lane detection model in Pytorch.
YOLOP - You Only Look Once for Panopitic Driving Perception.(MIR2022)
SNE-RoadSeg - SNE-RoadSeg for Freespace Detection in PyTorch, ECCV 2020
lanenet-lane-detection - Unofficial implemention of lanenet model for real time lane detection
Ultra-Fast-Lane-Detection vs Euro-Truck-Simulator-2-Lane-Assist
Ultra-Fast-Lane-Detection vs PaddleSeg
Ultra-Fast-Lane-Detection vs Ultrafast-Lane-Detection-Inference-Pytorch-
Ultra-Fast-Lane-Detection vs YOLOP
Ultra-Fast-Lane-Detection vs SNE-RoadSeg
Ultra-Fast-Lane-Detection vs lanenet-lane-detection