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3d-mininet

Official Implementation in Pytorch and Tensorflow of 3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation

3d-pointcloud

Papers and Datasets about Point Cloud.

albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

attention-transfer

Improving Convolutional Networks via Attention Transfer (ICLR 2017)

awesome-pruning

A curated list of neural network pruning resources.

bevfusion

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

birds-eye-view-perception

Awesome BEV perception research and cookbook for all level audience in autonomous diriving

cnnseg

CNNSeg Algorithm in APOLLO3.0

cop

Code for IJCAI2019 paper

cpgnet

cuda-pointpillars

A project demonstrating how to use CUDA-PointPillars to deal with cloud points data from lidar.

cuda-programming

Sample codes for my CUDA programming book

cuda_voxelizer

CUDA Voxelizer to convert polygon meshes into annotated voxel grids

cupcl

A project demonstrating how to use the libs of cuPCL.

cvpr2023-papers-with-code

CVPR 2023 论文和开源项目合集

dcnv2_trt

TensorRT plugin forDCNv2 layer in ONNX model

detr3d

eagleeye

(ECCV'2020 Oral)EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning

fast-cuda-gpu-dbscan

:star2: CUDA-DClust+: Fast DBSCAN algorithm implemented on CUDA. Based on the research paper.

fast-voxel-traversal-algorithm

A C++ implementation of the fast voxel traversal algorithm.

fast_lio

A computationally efficient and robust LiDAR-inertial odometry (LIO) package

filter-gap

The official PyTorch implementation of CHEX: CHannel EXploration for CNN Model Compression (CVPR 2022). Paper is available at https://openaccess.thecvf.com/content/CVPR2022/papers/Hou_CHEX_CHannel_EXploration_for_CNN_Model_Compression_CVPR_2022_paper.pdf

filter-pruning-geometric-median

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)

g-dbscan

CUDA implementation of DBSCAN. Inspired from paper https://www.sciencedirect.com/science/article/pii/S1877050913003438

g-vom

G-VOM: A GPU Accelerated Voxel Off-Road Mapping System

gdp

Tensorflow implementation for GDP.

greedy-layer-pruning

Greedy layer pruning for transformer models.

ground-segmentation-benchmark

Ground segmentation benchmark in SemanticKITTI dataset

halp

kd_lib

A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.