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Junyi Ma's Projects

cam4docc icon cam4docc

Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications

cvtnet icon cvtnet

[TII 2023] A Cross-View Transformer Network for LiDAR-Based Place Recognition in Autonomous Driving Environments.

deep-compression-pytorch icon deep-compression-pytorch

PyTorch implementation of 'Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding' by Song Han, Huizi Mao, William J. Dally

faiss icon faiss

A library for efficient similarity search and clustering of dense vectors.

glip icon glip

Grounded Language-Image Pre-training

gtsam icon gtsam

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.

lcpr icon lcpr

LCPR: A Multi-Scale Attention-Based LiDAR-Camera Fusion Network for Place Recognition

lidar-iris icon lidar-iris

LiDAR Iris for Loop-Closure Detection(IROS 2020)

lidar-mos icon lidar-mos

(LMNet) Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data (RAL/IROS 2021)

locus icon locus

This repository contains the code implementation used in the paper "Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling". Accepted for ICRA 2021.

lpd-net icon lpd-net

LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis, ICCV 2019, Seoul, Korea

mobilenetv3-tensorflow icon mobilenetv3-tensorflow

Unofficial implementation of MobileNetV3 architecture described in paper Searching for MobileNetV3.

moco icon moco

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

models icon models

Models and examples built with TensorFlow

ndt-transformer icon ndt-transformer

This github is a supplementary material including data, code, trained model and demo for the paper "NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation".

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