ciaochao's repositories
BEVFormer
[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
lift-splat-shoot
Lift, Splat, Shoot: Encoding Images from Arbitrary Camera Rigs by Implicitly Unprojecting to 3D (ECCV 2020)
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
SSD.Pytorch-1
Pytorch implementation of SSD512
PyTorch-YOLOv3
Minimal PyTorch implementation of YOLOv3
SSD
High quality, fast, modular reference implementation of SSD in PyTorch
pytorch-retinanet
Pytorch implementation of RetinaNet object detection.
ssd.pytorch
A PyTorch Implementation of Single Shot MultiBox Detector
pdarts
Codes for our paper "Progressive Differentiable Architecture Search:Bridging the Depth Gap between Search and Evaluation"
awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
MVision
机器人视觉 无人驾驶 视觉SLAM ORB LSD SVO DSO 深度学习目标检测yolov3 行为检测 opencv PCL 双目视觉
SSD-Tensorflow
Single Shot MultiBox Detector in TensorFlow
License-Plate-Detect-Recognition-via-Deep-Neural-Networks-accuracy-up-to-99.9
works in real-time with detection and recognition accuracy up to 99.8% for Chinese license plates: 100 ms/plate
MobileNetv2-SSDLite
Caffe implementation of SSD and SSDLite detection on MobileNetv2, converted from tensorflow.
Mobilenet_v2_ssd
mobilenet v2 for detection.
tensorpack
A Neural Net Training Interface on TensorFlow
SSD_for_Tensorflow
SSDSingle Shot MultiBox Detector目标检测算法基于tensorflow的实现
tf-pose-estimation
Deep Pose Estimation implemented using Tensorflow with Custom Architecture for fast inference.
priorbox_layer
use C++ to implement priorbox
mobile-deep-learning
This research aims at simply deploying CNN(Convolutional Neural Network) on mobile devices, with low complexity and high speed.
ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
FocalLoss
Caffe implementation of FAIR paper "Focal Loss for Dense Object Detection" for SSD.
caffe
Caffe: a fast open framework for deep learning.
MobileNet-SSD
Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.
depthwise_layer_caffe
Depthwise conv layer in caffe
shufflenet-ssd
shufflenet for object detection