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๐ #Selfdriving in 80's. Damn Romantic ๐
๐The first self-driving car with people on board, 1986. So slow and lovely.
More: https://bit.ly/3BtRDon
๐The first self-driving car with people on board, 1986. So slow and lovely.
More: https://bit.ly/3BtRDon
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๐ต๏ธ TORAS: SOTA #AI for annotation ๐ต๏ธ
๐TORAS: web-based AI-powered, cooperative, annotation platform.
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ SOTA AI tools -> significant speedup
โ "Recipes" to define how to annotate
โ Repo with folder structure for storage
โ Also on-prem for (commercial) firms
More: https://bit.ly/3L78YI2
๐TORAS: web-based AI-powered, cooperative, annotation platform.
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ SOTA AI tools -> significant speedup
โ "Recipes" to define how to annotate
โ Repo with folder structure for storage
โ Also on-prem for (commercial) firms
More: https://bit.ly/3L78YI2
๐ฅ9๐คฏ2๐1
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๐ฎMAXIM: Multi-Axis MLP for Vision๐ฎ
๐#Google opens MAXIM, a multi-axis MLP for low-level vision
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Denoising, deblurring, dehazing, etc
โ Multi-axis gated MLP, linear complexity
โ Cross gating block, separate features
โ SOTA results on several datasets!
More: https://bit.ly/3Dmp8LI
๐#Google opens MAXIM, a multi-axis MLP for low-level vision
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Denoising, deblurring, dehazing, etc
โ Multi-axis gated MLP, linear complexity
โ Cross gating block, separate features
โ SOTA results on several datasets!
More: https://bit.ly/3Dmp8LI
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๐ฅ A Survey on Diffusion Models ๐ฅ
๐A comprehensive review of denoising diffusion models in #computervision ๐คฏ
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Overview on diffusion models
โ Hot trend for the generative AI
โ A multi-perspective categorization
โ Current limitations / new directions
More: https://bit.ly/3RYG5zP
๐A comprehensive review of denoising diffusion models in #computervision ๐คฏ
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Overview on diffusion models
โ Hot trend for the generative AI
โ A multi-perspective categorization
โ Current limitations / new directions
More: https://bit.ly/3RYG5zP
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๐#AI finds where IG photos are taken๐
๐Brilliant work of Depoorter, Belgium artist that handles #privacy, #AI & #socialmedia
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Recorded open cameras for weeks
โ Scraped all #Instagram photos
โ Matching Instagram vs. footage
More: https://bit.ly/3eL5dfc
๐Brilliant work of Depoorter, Belgium artist that handles #privacy, #AI & #socialmedia
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Recorded open cameras for weeks
โ Scraped all #Instagram photos
โ Matching Instagram vs. footage
More: https://bit.ly/3eL5dfc
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๐ฏSAMURAI: in-the-wild Shape/Material๐ฏ
๐#Google SAMURAI: shape, BRDF, per-image pose & illumination. Relightable #3D assets for #AR/#VR.
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Parametrization for varying distances
โ Camera multiplex optimization
โ Posterior scaling of input images
โ Explicit meshes extraction with BRDF
โ Code/data soon available ->#NeurIPS
More: https://bit.ly/3BKWgf3
๐#Google SAMURAI: shape, BRDF, per-image pose & illumination. Relightable #3D assets for #AR/#VR.
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Parametrization for varying distances
โ Camera multiplex optimization
โ Posterior scaling of input images
โ Explicit meshes extraction with BRDF
โ Code/data soon available ->#NeurIPS
More: https://bit.ly/3BKWgf3
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๐จ Lang<->Pics in 100+ Languages ๐จ
๐#Google PaLI: unified lang-image #AI to perform tasks in 109 languages ๐คฏ
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ PaLI: Pathways Lang & Image model
โ Answering, captioning, reasoning, etc
โ From Eng. to 109 lang. understanding
โ The new SOTA on several datasets
More: https://bit.ly/3QMslHC
๐#Google PaLI: unified lang-image #AI to perform tasks in 109 languages ๐คฏ
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ PaLI: Pathways Lang & Image model
โ Answering, captioning, reasoning, etc
โ From Eng. to 109 lang. understanding
โ The new SOTA on several datasets
More: https://bit.ly/3QMslHC
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๐PeRFception: Largest IR Dataset๐
๐#Nvidia, a new frontier in data collection via Plenoxels: same info, -96.4% in size.
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ POSTECH + NVIDIA + Caltech = ๐คฏ
โ Size: -96.4% from original dataset!
โ 2D/3D image/object class/semantic
โ Ready-to-use pipeline for implicit dataset
More: https://bit.ly/3eW9hJA
๐#Nvidia, a new frontier in data collection via Plenoxels: same info, -96.4% in size.
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ POSTECH + NVIDIA + Caltech = ๐คฏ
โ Size: -96.4% from original dataset!
โ 2D/3D image/object class/semantic
โ Ready-to-use pipeline for implicit dataset
More: https://bit.ly/3eW9hJA
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๐ธ CHARL-E: Stable Diffusion in 1 click ๐ธ
๐CHARL-E packages Stable Diffusion into a simple app.
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ No setup, dependencies, or internet
โ Images with 1-click on #macbook
โ Suitable only for M1/M2 processor
โ Source code under MIT license
More: https://bit.ly/3xv2z3G
๐CHARL-E packages Stable Diffusion into a simple app.
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ No setup, dependencies, or internet
โ Images with 1-click on #macbook
โ Suitable only for M1/M2 processor
โ Source code under MIT license
More: https://bit.ly/3xv2z3G
๐ฅ11๐3โคโ๐ฅ1โค1
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๐YOLOPv2: Better Driving Perception๐
๐YOLOPv2: simultaneous object, road segmentation & lane detection
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ E2E perception net with better backbone
โ Efficient ELAN for reasonable memory
โ Stability for adapting to scenarios
โ SOTA on BDD100K, +50% faster!
โ Source code under MIT license
More: https://bit.ly/3LvYGBh
๐YOLOPv2: simultaneous object, road segmentation & lane detection
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ E2E perception net with better backbone
โ Efficient ELAN for reasonable memory
โ Stability for adapting to scenarios
โ SOTA on BDD100K, +50% faster!
โ Source code under MIT license
More: https://bit.ly/3LvYGBh
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๐SegNeXt: new SOTA in Semantic Seg.๐
๐SOTA (by large margin) on ADE20K, Cityscapes, COCO-Stuff, Pascal VOC, Pascal Context, and iSAID ๐คฏ
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Novel tailored network architecture
โ Spatial attention via multi-scale feats
โ Encoder + conv. better than transformers
โ SOTA on several datasets (ADE20K, etc.)
More: https://bit.ly/3UrZhrH
๐SOTA (by large margin) on ADE20K, Cityscapes, COCO-Stuff, Pascal VOC, Pascal Context, and iSAID ๐คฏ
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Novel tailored network architecture
โ Spatial attention via multi-scale feats
โ Encoder + conv. better than transformers
โ SOTA on several datasets (ADE20K, etc.)
More: https://bit.ly/3UrZhrH
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๐ฆชStereoVoxelNet: RT Obstacles Detection๐ฆช
๐Novel deep neural approach to detect occupancy from stereo images directly
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Occupancy voxels via deep learning
โ RT on Jetson-TX2 (-98% CPU of SOTA)
โ Optimization via octrees / sparse conv.
โ Real-world stereo in/outdoor dataset
More: https://bit.ly/3BylAn3
๐Novel deep neural approach to detect occupancy from stereo images directly
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Occupancy voxels via deep learning
โ RT on Jetson-TX2 (-98% CPU of SOTA)
โ Optimization via octrees / sparse conv.
โ Real-world stereo in/outdoor dataset
More: https://bit.ly/3BylAn3
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๐ NeRF-Factory: a NeRF collection ๐
๐PyTorch-reimplemented NeRF library with 7 popular models/implementations & 7 datasets
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ NeRF: Project | Paper | Code
โ NeRF++: Paper | Code
โ DVGO: Project | Paper v1/v2 | Code
โ Plenoxels: Project | Paper | Code
โ Mip-NeRF: Project | Paper | Code
โ Mip-NeRF360: Project | Paper | Code
โ Ref-NeRF: Project | Paper | Code
More: https://bit.ly/3qUgmgC
๐PyTorch-reimplemented NeRF library with 7 popular models/implementations & 7 datasets
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ NeRF: Project | Paper | Code
โ NeRF++: Paper | Code
โ DVGO: Project | Paper v1/v2 | Code
โ Plenoxels: Project | Paper | Code
โ Mip-NeRF: Project | Paper | Code
โ Mip-NeRF360: Project | Paper | Code
โ Ref-NeRF: Project | Paper | Code
More: https://bit.ly/3qUgmgC
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๐ฅถ Lumos by #Nvidia: Relighting Portrait ๐ฅถ
๐The new SOTA in relighting without requiring a light stage
๐Review https://bit.ly/3dCH9ej
๐Project deepimagination.cc/Lumos
๐Paper arxiv.org/pdf/2209.10510.pdf
๐Demo http://imaginaire.cc/Lumos/
๐The new SOTA in relighting without requiring a light stage
๐Review https://bit.ly/3dCH9ej
๐Project deepimagination.cc/Lumos
๐Paper arxiv.org/pdf/2209.10510.pdf
๐Demo http://imaginaire.cc/Lumos/
โค11๐1
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๐ SURF-GAN: NeRF - >StyleGAN ๐
๐ Editable portraits by injecting the NeRF's prior into StyleGAN
๐Review https://bit.ly/3SohEw3
๐Project jgkwak95.github.io/surfgan
๐Paper arxiv.org/pdf/2207.10257.pdf
๐Code github.com/jgkwak95/SURF-GAN
๐ Editable portraits by injecting the NeRF's prior into StyleGAN
๐Review https://bit.ly/3SohEw3
๐Project jgkwak95.github.io/surfgan
๐Paper arxiv.org/pdf/2207.10257.pdf
๐Code github.com/jgkwak95/SURF-GAN
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๐ฅ#Google just announced "TensorStore"๐ฅ
๐Novel open-source C++ / #Python library for storage/manipulation of high-dim data
๐Review https://bit.ly/3DLwbha
๐Project https://bit.ly/3C4T2TR
๐Code github.com/google/tensorstore
๐Novel open-source C++ / #Python library for storage/manipulation of high-dim data
๐Review https://bit.ly/3DLwbha
๐Project https://bit.ly/3C4T2TR
๐Code github.com/google/tensorstore
๐ฅ14๐2
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๐ฆ Motion Transformer for #selfdriving ๐ฆ
๐The 1st place solution for 2022 #waymo "motion prediction" challenge
๐Review https://bit.ly/3f8G4LD
๐Paper arxiv.org/pdf/2209.10033.pdf
๐Code github.com/sshaoshuai/MTR
๐The 1st place solution for 2022 #waymo "motion prediction" challenge
๐Review https://bit.ly/3f8G4LD
๐Paper arxiv.org/pdf/2209.10033.pdf
๐Code github.com/sshaoshuai/MTR
๐ฅ17๐3
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๐น Image Synthesis @160+ FPS! ๐น
๐Super-fast, 3D-Aware Image Synthesis with Sparse Voxels -> up to 167 FPS!
๐Review https://bit.ly/3r3ZNij
๐Paper arxiv.org/pdf/2206.07695.pdf
๐Project katjaschwarz.github.io/voxgraf
๐Super-fast, 3D-Aware Image Synthesis with Sparse Voxels -> up to 167 FPS!
๐Review https://bit.ly/3r3ZNij
๐Paper arxiv.org/pdf/2206.07695.pdf
๐Project katjaschwarz.github.io/voxgraf
๐3๐คฏ2๐ฅ1๐ฏ1
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๐ #Nvidia GET3D: #3D generative #AI ๐
๐AI-based Textured 3D meshes with complex topology, rich geometry & hi-fi textures
๐Review https://bit.ly/3SgnT5h
๐Code github.com/nv-tlabs/GET3D
๐Project nv-tlabs.github.io/GET3D/
๐Paper nv-tlabs.github.io/GET3D/assets/paper.pdf
๐AI-based Textured 3D meshes with complex topology, rich geometry & hi-fi textures
๐Review https://bit.ly/3SgnT5h
๐Code github.com/nv-tlabs/GET3D
๐Project nv-tlabs.github.io/GET3D/
๐Paper nv-tlabs.github.io/GET3D/assets/paper.pdf
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