cndylan

cndylan

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cndylan's repositories

ResNeXt

Reproduce ResNet-v3(Aggregated Residual Transformations for Deep Neural Network) with Caffe

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ademxapp

Code for https://arxiv.org/abs/1611.10080

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affordance-net

AffordanceNet - Multiclass Instance Segmentation Framework - ICRA 2018

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caffe-fast-rcnn

Caffe fork that supports Fast R-CNN

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da-faster-rcnn

An implementation of our CVPR 2018 work 'Domain Adaptive Faster R-CNN for Object Detection in the Wild'

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darts

Differentiable architecture search for convolutional and recurrent networks

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deep_architect

A general, modular, and programmable architecture search framework

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Detect-Track

Code release for "Detect to Track and Track to Detect", ICCV 2017

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finetune_alexnet_with_tensorflow

Code for finetuning AlexNet in TensorFlow >= 1.12

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frustum-pointnets

Frustum PointNets for 3D Object Detection from RGB-D Data

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go-vncdriver

Fast VNC driver

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light_head_rcnn

Light-Head R-CNN

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Mask-RCNN

Implementation of Mask-RCNN in Caffe https://arxiv.org/pdf/1703.06870.pdf

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MegEngine

MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架

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MonoGRNet

MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Detection and Localization | KITTI

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mx-maskrcnn

A MXNet implementation of Mask R-CNN

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nuscenes-devkit

The dev-kit of the nuScenes dataset.

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pcn

Code for PCN: Point Completion Network in 3DV'18 (Oral)

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pointSIFT

a module for 3D semantic segmentation in point clouds.

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py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

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second.pytorch

PointPillars for KITTI object detection

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stable-diffusion

A latent text-to-image diffusion model

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tensorpack

A Neural Net Training Interface on TensorFlow

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Unsupervised_Depth_Estimation

Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

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vega

AutoML tools chain

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vid2vid

Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.

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Yet-Another-EfficientDet-Pytorch

The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

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