Popular GitHub Repositories for Hi3516dv300

Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Transformer" and SuperCluster introduced in [3DV'24 Oral] "Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering"

3DV 2021: Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

SPIGA: Shape Preserving Facial Landmarks with Graph Attention Networks.

? Tidal Music. No account required.

A P300 online spelling mechanism for Emotiv headsets. It's completely written in Node.js, and the GUI is based on Electron and Vue.

C.Origami, a prediction and screening framework for cell type-specific 3D chromatin structure.

Hello everyone this repo will contain my journey of machine learning and DeepLearning with some exciting projects

Universal Joint Feature Extraction for P300 EEG Classification Using Multi-Task Autoencoder (IEEE Access)

[3DV21] Visual Camera Re-Localization Using Graph Neural Networks and Relative Pose Supervision, M. Türko?lu et al.

Official Repository for "Diffusion HPC: Generate Synthetic Data for Human Mesh Recovery in Challenging Domains" (3DV 2024 Spotlight)

Geometric Adversarial Attacks and Defenses on 3D Point Clouds (3DV 2021)

人脸识别终端（Qt版本）

A Generalizable Model for 3D Chromosome Reconstruction Using Graph Convolutional Neural Networks

? Automated deployment stack for AMD MI300 GPUs with optimized ML/DL frameworks and HPC-ready configurations

This repository contains an experimental demo application that shows how you can add client-side auto-generated captions to Amazon IVS Real-time and Low-latency streams using transformers.js and WebGPU.

This project trains a SSD300 with VGG11 base on the PASCAL VOC 2005 dataset using the PyTorch deep learning framework.

Training neural network weights in a bitwise fashion: https://arxiv.org/abs/2202.09571

? Automated installation script for vLLM on HPC systems with ROCm support, optimized for AMD MI300X GPUs.

TapeShift: A Bash script optimized for MacOS with features to digitize camcorder footage for editing in Davinci Resolve.

Research datasets and experimental results from comprehensive ML benchmarking on AMD MI300X hardware. Contains raw telemetry, processed metrics, and reproducible analysis artifacts from both inference and training workloads, supporting research and comparative studies.