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attmpti

[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation

changeable_region_detection

A changeable region detection method based on yolov5

cola

Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning (CoLA), TNNLS-21

crosspoint

Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

crosspoint_june

diffusion-models-papers-survey-taxonomy

Diffusion model papers, survey, and taxonomy

fastestdet

:zap: A newly designed ultra lightweight anchor free target detection algorithm， weight only 250K parameters， reduces the time consumption by 10% compared with yolo-fastest, and the post-processing is simpler

gacnet

Pytorch implementation of 'Graph Attention Convolution for Point Cloud Segmentation'

gnn-points-cloud

graph-wavenet

graph wavenet

machine_learning1.15

merit

A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning", IJCAI-21

molclr

Implementation of "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyTorch Geometric

my_moco_pointnet-_1.0

pct

Jittor implementation of PCT:Point Cloud Transformer

pointaugment

Code for PointAugment: an Auto-Augmentation Framework for Point Cloud Classification, CVPR 2020 (Oral)

pointflow

PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flows

pointnet.pytorch

pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593

pyqt5_yolov5_unet_centernet

集yolov5、centernet、unet算法的pyqt5界面，可实现图片目标检测和语义分割

pytorch_geometric

Graph Neural Network Library for PyTorch

pytorch_learning

seed-weights

tensorflow_object_counting_api

🚀 The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems!

unbox_yolov5_deepsort_counting

yolov5 deepsort 行人 车辆 跟踪 检测 计数

video2images

wavenet

Yet another WaveNet implementation in PyTorch.

yolo-fastest

:zap: Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+

yolo-fastestv2

:zap: Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

yoloair

🔥🔥🔥YOLOv5, YOLOv6, YOLOv7, PPYOLOE, YOLOX, YOLOR, YOLOv4, YOLOv3, PPYOLO, PPYOLOv2, Transformer, Attention, TOOD and Improved-YOLOv5-YOLOv7... Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀

yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite