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Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
https://nvlabs.github.io/denoising-diffusion-gan/
Paper: https://arxiv.org/pdf/2112.07804.pdf
Code: https://github.com/NVlabs/denoising-diffusion-gan
@ArtificialIntelligencedl
https://nvlabs.github.io/denoising-diffusion-gan/
Paper: https://arxiv.org/pdf/2112.07804.pdf
Code: https://github.com/NVlabs/denoising-diffusion-gan
@ArtificialIntelligencedl
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Github: https://github.com/Arthur151/ROMP
Paper: https://arxiv.org/abs/2112.08274v1
Dataset: https://paperswithcode.com/dataset/agora
@ArtificialIntelligencedl
Github: https://github.com/Arthur151/ROMP
Paper: https://arxiv.org/abs/2112.08274v1
Dataset: https://paperswithcode.com/dataset/agora
@ArtificialIntelligencedl
PECOS - Predictions for Enormous and Correlated Output Spaces
Github: https://github.com/amzn/pecos
Paper: https://arxiv.org/abs/2112.08652v1
@ArtificialIntelligencedl
Github: https://github.com/amzn/pecos
Paper: https://arxiv.org/abs/2112.08652v1
@ArtificialIntelligencedl
🚀 SeqFormer: a Frustratingly Simple Model for Video Instance Segmentation
Github: https://github.com/wjf5203/SeqFormer
Paper: https://arxiv.org/pdf/2112.08275v1.pdf
Datasett: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
Github: https://github.com/wjf5203/SeqFormer
Paper: https://arxiv.org/pdf/2112.08275v1.pdf
Datasett: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
⚙️ StyleSwin: Transformer-based GAN for High-resolution Image Generation
Github: https://github.com/microsoft/StyleSwin
Paper: https://arxiv.org/abs/2112.10762
@ArtificialIntelligencedl
Github: https://github.com/microsoft/StyleSwin
Paper: https://arxiv.org/abs/2112.10762
@ArtificialIntelligencedl
Cost Aggregation Is All You Need for Few-Shot Segmentation
Github: https://github.com/Seokju-Cho/Volumetric-Aggregation-Transformer
Paper: https://arxiv.org/pdf/2112.11685v1.pdf
Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
Github: https://github.com/Seokju-Cho/Volumetric-Aggregation-Transformer
Paper: https://arxiv.org/pdf/2112.11685v1.pdf
Dataset: https://paperswithcode.com/dataset/coco
@ArtificialIntelligencedl
🔼 Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughs
Github: https://github.com/cmusatyalab/mega-nerf
Paper: https://arxiv.org/pdf/2112.11685v1.pdf
Dataset: https://paperswithcode.com/dataset/urbanscene3d
@ArtificialIntelligencedl
Github: https://github.com/cmusatyalab/mega-nerf
Paper: https://arxiv.org/pdf/2112.11685v1.pdf
Dataset: https://paperswithcode.com/dataset/urbanscene3d
@ArtificialIntelligencedl
JoJoGAN: One Shot Face Stylization
Github: https://github.com/mchong6/JoJoGAN
Paper: https://arxiv.org/pdf/2112.11685v1.pdf
Tasks: https://paperswithcode.com/task/face-generation
@ArtificialIntelligencedl
Github: https://github.com/mchong6/JoJoGAN
Paper: https://arxiv.org/pdf/2112.11685v1.pdf
Tasks: https://paperswithcode.com/task/face-generation
@ArtificialIntelligencedl
🎭 SeMask: Semantically Masked Transformers for Semantic Segmentation
Github: https://github.com/Picsart-AI-Research/SeMask-Segmentation
Paper: https://arxiv.org/abs/2112.12782
Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
Github: https://github.com/Picsart-AI-Research/SeMask-Segmentation
Paper: https://arxiv.org/abs/2112.12782
Dataset: https://paperswithcode.com/dataset/cityscapes
@ArtificialIntelligencedl
📍 SLIP: Self-supervision meets Language-Image Pre-training
Github: https://github.com/facebookresearch/slip
Paper: https://arxiv.org/abs/2112.12750v1
Dataset: https://paperswithcode.com/dataset/kitti
@ArtificialIntelligencedl
Github: https://github.com/facebookresearch/slip
Paper: https://arxiv.org/abs/2112.12750v1
Dataset: https://paperswithcode.com/dataset/kitti
@ArtificialIntelligencedl
🔎 PyCIL: A Python Toolbox for Class-Incremental Learning
Github: https://github.com/g-u-n/pycil
Paper: https://arxiv.org/abs/2112.12533v1
Dataset: https://paperswithcode.com/dataset/cifar-100
@ArtificialIntelligencedl
Github: https://github.com/g-u-n/pycil
Paper: https://arxiv.org/abs/2112.12533v1
Dataset: https://paperswithcode.com/dataset/cifar-100
@ArtificialIntelligencedl
Block Modeling-Guided Graph Convolutional Neural Networks
Github: https://github.com/hedongxiao-tju/BM-GCN
Paper: https://arxiv.org/abs/2112.13507v1
Dataset: https://paperswithcode.com/dataset/pubmed
@ArtificialIntelligencedl
Github: https://github.com/hedongxiao-tju/BM-GCN
Paper: https://arxiv.org/abs/2112.13507v1
Dataset: https://paperswithcode.com/dataset/pubmed
@ArtificialIntelligencedl
Evolutionary Generation of Visual Motion Illusions
Github: https://github.com/LanaSina/evolutionary_illusion_generator
Paper: https://arxiv.org/abs/2112.13243v1
Dataset: https://paperswithcode.com/dataset/prednet-grayscale-model-weights
@ArtificialIntelligencedl
Github: https://github.com/LanaSina/evolutionary_illusion_generator
Paper: https://arxiv.org/abs/2112.13243v1
Dataset: https://paperswithcode.com/dataset/prednet-grayscale-model-weights
@ArtificialIntelligencedl
GitHub
evolutionary_illusion_generator/_EIGen.png at master · LanaSina/evolutionary_illusion_generator
EIGen: Evolutionary Illusion Generator, based on predictive coding. - LanaSina/evolutionary_illusion_generator
👁 Vision Transformer for Small-Size Datasets
Github: https://github.com/LanaSina/evolutionary_illusion_generator
Paper: https://arxiv.org/abs/2112.13492
Dataset: https://paperswithcode.com/dataset/tiny-imagenet
@ArtificialIntelligencedl
Github: https://github.com/LanaSina/evolutionary_illusion_generator
Paper: https://arxiv.org/abs/2112.13492
Dataset: https://paperswithcode.com/dataset/tiny-imagenet
@ArtificialIntelligencedl
Towards continual task learning in artificial neural networks: current approaches and insights from neuroscience
Github: https://github.com/mccaffary/continual-learning
Paper: https://arxiv.org/pdf/2112.14146v1.pdf
Tasks: https://paperswithcode.com/task/continual-learning
@ArtificialIntelligencedl
Github: https://github.com/mccaffary/continual-learning
Paper: https://arxiv.org/pdf/2112.14146v1.pdf
Tasks: https://paperswithcode.com/task/continual-learning
@ArtificialIntelligencedl
Forwarded from Data Science
Deep Learning Interviews book: Hundreds of fully solved job interview questions from a wide range of key topics in AI
📖 Book
@datascienceiot
📖 Book
@datascienceiot
A Transformer-Based Siamese Network for Change Detection
Github: https://github.com/wgcban/changeformer
Paper: https://arxiv.org/abs/2201.01293v1
@ArtificialIntelligencedl
Github: https://github.com/wgcban/changeformer
Paper: https://arxiv.org/abs/2201.01293v1
@ArtificialIntelligencedl
Minimum Viable Study Plan for Machine Learning Interviews
https://github.com/khangich/machine-learning-interview
@ArtificialIntelligencedl
https://github.com/khangich/machine-learning-interview
@ArtificialIntelligencedl
GitHub
GitHub - khangich/machine-learning-interview: Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat…
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io. - khangich/machine-learning-interview
✔️ Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow.
Github: https://github.com/qubvel/segmentation_models
Paper: https://arxiv.org/abs/2201.02107v1
Tasks: https://paperswithcode.com/task/semantic-segmentation
@ArtificialIntelligencedl
Github: https://github.com/qubvel/segmentation_models
Paper: https://arxiv.org/abs/2201.02107v1
Tasks: https://paperswithcode.com/task/semantic-segmentation
@ArtificialIntelligencedl
HuSpaCy: Industrial-strength Hungarian NLP
Github: https://github.com/huspacy/huspacy
Paper: https://arxiv.org/abs/2201.01956v1
Dataset: https://paperswithcode.com/dataset/universal-dependencies
@ArtificialIntelligencedl
Github: https://github.com/huspacy/huspacy
Paper: https://arxiv.org/abs/2201.01956v1
Dataset: https://paperswithcode.com/dataset/universal-dependencies
@ArtificialIntelligencedl
GitHub
GitHub - huspacy/huspacy: HuSpaCy: industrial-strength Hungarian natural language processing
HuSpaCy: industrial-strength Hungarian natural language processing - huspacy/huspacy
🚶 Pedestron is a MMdetection based repository, that focuses on the advancement of research on pedestrian detection.
Github: https://github.com/hasanirtiza/Pedestron
Paper: https://arxiv.org/abs/2201.03176v1
Dataset: https://paperswithcode.com/dataset/citypersons
@ArtificialIntelligencedl
Github: https://github.com/hasanirtiza/Pedestron
Paper: https://arxiv.org/abs/2201.03176v1
Dataset: https://paperswithcode.com/dataset/citypersons
@ArtificialIntelligencedl