awesome-citygmlThe ultimate list of open data semantic city models
Stars: ✭ 57 (+256.25%)
Mutual labels: 3d-models
redcubeJS renderer based on GLTF to WebGPU or WebGL backends.
Stars: ✭ 86 (+437.5%)
Mutual labels: 3d-models
ecad-modelsRandom 3D models and such for CAD/ECAD
Stars: ✭ 18 (+12.5%)
Mutual labels: 3d-models
AU RecognitionAU_Recognition based on CKPlus/CK database
Stars: ✭ 21 (+31.25%)
Mutual labels: transfer-learning
StickMan-3DStickMan 3D: First Round | indie fighting game | C++ OpenGL
Stars: ✭ 60 (+275%)
Mutual labels: 3d-models
MetaHeacThis is an official implementation for "Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising"(KDD2021).
Stars: ✭ 36 (+125%)
Mutual labels: transfer-learning
floor3d-cardYour Home Digital Twin: aka floor3d-card. Visualize Home Assistant state and perform actions using objects in a 3D home model based on Three.js.
Stars: ✭ 237 (+1381.25%)
Mutual labels: 3d-models
tamnun-mlAn easy to use open-source library for advanced Deep Learning and Natural Language Processing
Stars: ✭ 109 (+581.25%)
Mutual labels: transfer-learning
Open set domain adaptationTensorflow Implementation of open set domain adaptation by backpropagation
Stars: ✭ 27 (+68.75%)
Mutual labels: transfer-learning
super-gradientsEasily train or fine-tune SOTA computer vision models with one open source training library
Stars: ✭ 429 (+2581.25%)
Mutual labels: transfer-learning
TrainCaffeCustomDatasetTransfer learning in Caffe: example on how to train CaffeNet on custom dataset
Stars: ✭ 20 (+25%)
Mutual labels: transfer-learning
CPCE-3DLow-dose CT via Transfer Learning from a 2D Trained Network, In IEEE TMI 2018
Stars: ✭ 40 (+150%)
Mutual labels: transfer-learning
translearnCode implementation of the paper "With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning", at USENIX Security 2018
Stars: ✭ 18 (+12.5%)
Mutual labels: transfer-learning
StlVault3D object viewer and organizer
Stars: ✭ 104 (+550%)
Mutual labels: 3d-models
DANCode release of "Learning Transferable Features with Deep Adaptation Networks" (ICML 2015)
Stars: ✭ 149 (+831.25%)
Mutual labels: transfer-learning
voxelizer👾 Voxelization of 3D models
Stars: ✭ 32 (+100%)
Mutual labels: 3d-models
Music-Genre-ClassificationGenre Classification using Convolutional Neural Networks
Stars: ✭ 27 (+68.75%)
Mutual labels: transfer-learning
3-D-Scene-Graph3D scene graph generator implemented in Pytorch.
Stars: ✭ 52 (+225%)
Mutual labels: 3d-models