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mobilestereonet

Lightweight stereo matching network based on MobileNet blocks

monodepth2

[ICCV 2019] Monocular depth estimation from a single image

monodepth2_rknn

monoformer

mtcnn-pytorch

A face detection algorithm

ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

ncnn-android-yolov5

ncnn, android, and Yolov5

ncnn-android-yolov5-static

The YOLOv5 object detection android example

network-slimming-keras

Implementation of "Learning Efficient Convolutional Networks through Network Slimming" (ICCV2017)

object_detection_evaluation

onnx-crestereo-depth-estimation

Python scripts performing stereo depth estimation using the CREStereo model in ONNX.

paddledetection

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

painter

Painter & SegGPT Series: Vision Foundation Models from BAAI

pinto_model_zoo

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

psmnet

Pyramid Stereo Matching Network (CVPR2018)

pytorch-yolov4

raft-stereo

real-time-self-adaptive-deep-stereo

Code for "Real-time self-adaptive deep stereo" - CVPR 2019 (ORAL)

sc-depthv3_rknn

sc_depth_pl

SC-Depth (V1, V2, and V3) for Unsupervised Monocular Depth Estimation Webpage:https://jiawangbian.github.io/sc_depth_pl/

scripts

smd-nets

SMD-Nets: Stereo Mixture Density Networks

snpe-yolov7-inference

A yolov7 tiny model inference applied on qualcomm snpe for pedestrian detection with embedded system.

stereonet

A customized implementation of the paper "StereoNet: guided hierarchical refinement for real-time edge-aware depth prediction"

stereonet_friggog

stereonet_pytorch

StereoNet PyTorch Lightning

stereonet_rknn

superpoint2cpp

The C++ implementation of SuperPoint

superpoint_a311d

tengine

Tengine is a lite, high performance, modular inference engine for embedded device