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caffe

Caffe: a fast open framework for deep learning.

caffe-fast-rcnn

Caffe fork that supports Fast R-CNN

caffe-faster-rcnn

faster rcnn c++ version. joint train; please checkout into dev branch (git checkout dev)

caffe-rfcn

Caffe branch for R-FCN

caffe_yolov2

YOLOv2 object detection based on Caffe

cascade-rcnn_pytorch

An implementation of Cascade R-CNN: Delving into High Quality Object Detection.

ccpd

[ECCV 2018] CCPD: a diverse and well-annotated dataset for license plate detection and recognition

centerformer

Implementation for CenterFormer: Center-based Transformer for 3D Object Detection (ECCV 2022)

centerpoint

chainer-visualization

Chainer implementation of the paper Visualizing and Understanding Convolutional Networks, 2013

codetricks

一些奇技淫巧，just for fun

computelibrary

The ARM Computer Vision and Machine Learning library is a set of functions optimised for both ARM CPUs and GPUs using SIMD technologies.

coreutils

upstream mirror

crnn-keras

CRNN (CNN+RNN) for OCR using Keras / License Plate Recognition

cuda-convnet2

Automatically exported from code.google.com/p/cuda-convnet2

cunn

cylinder3d

Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)

dab-detr

[ICLR 2022] DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR

dair_v2x_i_dataset_vis

For visualizing the dair-v2x-i dataset

darknet

Convolutional Neural Networks

dasiamrpn

[ECCV2018] Distractor-aware Siamese Networks for Visual Object Tracking

deep-alignment-network-a-convolutional-neural-network-for-robust-face-alignment

This is a Tensorflow implementations of paper "Deep Alignment Network: A convolutional neural network for robust face alignment".

deep-residual-networks

Deep Residual Learning for Image Recognition

deep_sort_pytorch

MOT tracking using deepsort and yolov3 with pytorch

deep_sort_yolov3

Real-time Multi-person tracker using YOLO v3 and deep_sort with tensorflow

deepdraw

Notebook example of how to generate class visualizations with Caffe

deepdream

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

deformable-detr

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.