A comprehensive list of Implicit Representations, NeRF and 3D Gaussian Splatting papers relating to SLAM/Robotics domain, including papers, videos, codes, and related websites

📍PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving Global Map Consistency [TRO' 24]

[3DV 2022] GO-Surf: Neural Feature Grid Optimization for Fast, High-Fidelity RGB-D Surface Reconstruction

[NeurIPS'2024] Neural Signed Distance Function Inference through Splatting 3D Gaussians Pulled on Zero-Level Set

Neural Unsigned Distance Fields (NDF) - Codebase

Real-time Neural Signed Distance Fields for Robot Perception

SuperPoint and SuperGlue with TensorRT. Deploy with C++.

Implementation of ICCV19 Paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network"

a reimplementation of Holistically-Nested Edge Detection in PyTorch

Correspondence points annotation tool

tensorrt for yolo series (YOLOv11,YOLOv10,YOLOv9,YOLOv8,YOLOv7,YOLOv6,YOLOX,YOLOv5), nms plugin support

[ECCV 2024] RGBD GS-ICP SLAM

Paper reading notes on Deep Learning and Machine Learning

Dense matching library based on PyTorch

Implementation of End-to-End YOLO Models for DeepStream

Implementation of Nvidia DeepStream 7 with YOLOv9 Models.

This repository serves as an example of deploying the YOLO models on Triton Server for performance and testing purposes

NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

JAX-Toolbox

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

A playbook for systematically maximizing the performance of deep learning models.

Triton backend that enables pre-process, post-processing and other logic to be implemented in Python.

The Triton backend that allows running GPU-accelerated data pre-processing pipelines implemented in DALI's python API.

This repository contains tutorials and examples for Triton Inference Server

Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX

Nvidia Semantic Segmentation monorepo

Image augmentation for machine learning experiments.

Label Objects and Save Time (LOST) - Design your own smart Image Annotation process in a web-based environment.

Adaptions of pylessons repo for yolo training (https://github.com/pythonlessons/TensorFlow-2.x-YOLOv3)