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[CVPR 2023 Workshop] VAND Challenge: 1st Place on Zero-shot AD and 4th Place on Few-shot AD
[CVPR 2023] Unofficial re-implementation of "WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation".
[ICLR 2024 Oral] Generative Gaussian Splatting for Efficient 3D Content Creation
计算机类常用电子书整理，并且附带下载链接，包括Java，Python，Linux，Go，C，C++，数据结构与算法，人工智能，计算机基础，面试，设计模式，数据库，前端等书籍
涵盖C++ Primer 5th、 effective C++ 、 STL api和demos C++ 基础知识与理论、 智能指针、C++11、 Git教程 Linux命令 Unix操作系统（进程、线程、内存管理、信号）计算机网络、 数据结构（排序、查找）、数据库、、C++对象模型、 设计模式、算法（《剑指offer》、leetcode、lintcode、hihocoder、《王道程序员求职…
Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translatio…
A simple version for graphfpn
PyTorch implementation of Non-Local Neural Networks (https://arxiv.org/pdf/1711.07971.pdf)
maskrcnn with Latent Graph Neural Network, experiments of "LatentGNN"(ICML2019)
Repo for "Graph-based Object Classification for Neuromorphic Vision Sensing" ICCV2019
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org
links to conference publications in graph-based deep learning
Implementation of “LatentGNN: Learning Efficient Non-local Relations for Visual Recognition”(ICML 2019)
This is the official implemntation for "Multi-scale spatial temporal graph convolutional network for skeleton-based action recognition" AAAI-2021
Must-read papers on graph neural networks (GNN)
Implementation of our AAAI'22 work: 'UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer'.
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Turkish using the Common Voice
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Tencent Cloud API 3.0 SDK for Python
Google Summer of Code 2018 Project: Automatic Speech Recognition for Speech-to-Text on Chinese
Chinese Speech To Text Using Wavenet
Java 9 port of the ADPCM-XQ encoder/decoder library.