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π#AI finds where IG photos are takenπ
πBrilliant work of Depoorter, Belgium artist that handles #privacy, #AI & #socialmedia
ππ’π π‘π₯π’π π‘ππ¬:
β Recorded open cameras for weeks
β Scraped all #Instagram photos
β Matching Instagram vs. footage
More: https://bit.ly/3eL5dfc
πBrilliant work of Depoorter, Belgium artist that handles #privacy, #AI & #socialmedia
ππ’π π‘π₯π’π π‘ππ¬:
β Recorded open cameras for weeks
β Scraped all #Instagram photos
β Matching Instagram vs. footage
More: https://bit.ly/3eL5dfc
π±18π13π₯°2
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π―SAMURAI: in-the-wild Shape/Materialπ―
π#Google SAMURAI: shape, BRDF, per-image pose & illumination. Relightable #3D assets for #AR/#VR.
ππ’π π‘π₯π’π π‘ππ¬:
β Parametrization for varying distances
β Camera multiplex optimization
β Posterior scaling of input images
β Explicit meshes extraction with BRDF
β Code/data soon available ->#NeurIPS
More: https://bit.ly/3BKWgf3
π#Google SAMURAI: shape, BRDF, per-image pose & illumination. Relightable #3D assets for #AR/#VR.
ππ’π π‘π₯π’π π‘ππ¬:
β Parametrization for varying distances
β Camera multiplex optimization
β Posterior scaling of input images
β Explicit meshes extraction with BRDF
β Code/data soon available ->#NeurIPS
More: https://bit.ly/3BKWgf3
π8π₯1
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π¨ Lang<->Pics in 100+ Languages π¨
π#Google PaLI: unified lang-image #AI to perform tasks in 109 languages π€―
ππ’π π‘π₯π’π π‘ππ¬:
β PaLI: Pathways Lang & Image model
β Answering, captioning, reasoning, etc
β From Eng. to 109 lang. understanding
β The new SOTA on several datasets
More: https://bit.ly/3QMslHC
π#Google PaLI: unified lang-image #AI to perform tasks in 109 languages π€―
ππ’π π‘π₯π’π π‘ππ¬:
β PaLI: Pathways Lang & Image model
β Answering, captioning, reasoning, etc
β From Eng. to 109 lang. understanding
β The new SOTA on several datasets
More: https://bit.ly/3QMslHC
π₯6π1π―1
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πPeRFception: Largest IR Datasetπ
π#Nvidia, a new frontier in data collection via Plenoxels: same info, -96.4% in size.
ππ’π π‘π₯π’π π‘ππ¬:
β POSTECH + NVIDIA + Caltech = π€―
β Size: -96.4% from original dataset!
β 2D/3D image/object class/semantic
β Ready-to-use pipeline for implicit dataset
More: https://bit.ly/3eW9hJA
π#Nvidia, a new frontier in data collection via Plenoxels: same info, -96.4% in size.
ππ’π π‘π₯π’π π‘ππ¬:
β POSTECH + NVIDIA + Caltech = π€―
β Size: -96.4% from original dataset!
β 2D/3D image/object class/semantic
β Ready-to-use pipeline for implicit dataset
More: https://bit.ly/3eW9hJA
β€9β€βπ₯1π1π1
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πΈ CHARL-E: Stable Diffusion in 1 click πΈ
πCHARL-E packages Stable Diffusion into a simple app.
ππ’π π‘π₯π’π π‘ππ¬:
β No setup, dependencies, or internet
β Images with 1-click on #macbook
β Suitable only for M1/M2 processor
β Source code under MIT license
More: https://bit.ly/3xv2z3G
πCHARL-E packages Stable Diffusion into a simple app.
ππ’π π‘π₯π’π π‘ππ¬:
β No setup, dependencies, or internet
β Images with 1-click on #macbook
β Suitable only for M1/M2 processor
β Source code under MIT license
More: https://bit.ly/3xv2z3G
π₯11π3β€βπ₯1β€1
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πYOLOPv2: Better Driving Perceptionπ
πYOLOPv2: simultaneous object, road segmentation & lane detection
ππ’π π‘π₯π’π π‘ππ¬:
β E2E perception net with better backbone
β Efficient ELAN for reasonable memory
β Stability for adapting to scenarios
β SOTA on BDD100K, +50% faster!
β Source code under MIT license
More: https://bit.ly/3LvYGBh
πYOLOPv2: simultaneous object, road segmentation & lane detection
ππ’π π‘π₯π’π π‘ππ¬:
β E2E perception net with better backbone
β Efficient ELAN for reasonable memory
β Stability for adapting to scenarios
β SOTA on BDD100K, +50% faster!
β Source code under MIT license
More: https://bit.ly/3LvYGBh
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πSegNeXt: new SOTA in Semantic Seg.π
πSOTA (by large margin) on ADE20K, Cityscapes, COCO-Stuff, Pascal VOC, Pascal Context, and iSAID π€―
ππ’π π‘π₯π’π π‘ππ¬:
β Novel tailored network architecture
β Spatial attention via multi-scale feats
β Encoder + conv. better than transformers
β SOTA on several datasets (ADE20K, etc.)
More: https://bit.ly/3UrZhrH
πSOTA (by large margin) on ADE20K, Cityscapes, COCO-Stuff, Pascal VOC, Pascal Context, and iSAID π€―
ππ’π π‘π₯π’π π‘ππ¬:
β Novel tailored network architecture
β Spatial attention via multi-scale feats
β Encoder + conv. better than transformers
β SOTA on several datasets (ADE20K, etc.)
More: https://bit.ly/3UrZhrH
π₯9π1
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π¦ͺStereoVoxelNet: RT Obstacles Detectionπ¦ͺ
πNovel deep neural approach to detect occupancy from stereo images directly
ππ’π π‘π₯π’π π‘ππ¬:
β Occupancy voxels via deep learning
β RT on Jetson-TX2 (-98% CPU of SOTA)
β Optimization via octrees / sparse conv.
β Real-world stereo in/outdoor dataset
More: https://bit.ly/3BylAn3
πNovel deep neural approach to detect occupancy from stereo images directly
ππ’π π‘π₯π’π π‘ππ¬:
β Occupancy voxels via deep learning
β RT on Jetson-TX2 (-98% CPU of SOTA)
β Optimization via octrees / sparse conv.
β Real-world stereo in/outdoor dataset
More: https://bit.ly/3BylAn3
π10π₯°1
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π NeRF-Factory: a NeRF collection π
πPyTorch-reimplemented NeRF library with 7 popular models/implementations & 7 datasets
ππ’π π‘π₯π’π π‘ππ¬:
β NeRF: Project | Paper | Code
β NeRF++: Paper | Code
β DVGO: Project | Paper v1/v2 | Code
β Plenoxels: Project | Paper | Code
β Mip-NeRF: Project | Paper | Code
β Mip-NeRF360: Project | Paper | Code
β Ref-NeRF: Project | Paper | Code
More: https://bit.ly/3qUgmgC
πPyTorch-reimplemented NeRF library with 7 popular models/implementations & 7 datasets
ππ’π π‘π₯π’π π‘ππ¬:
β NeRF: Project | Paper | Code
β NeRF++: Paper | Code
β DVGO: Project | Paper v1/v2 | Code
β Plenoxels: Project | Paper | Code
β Mip-NeRF: Project | Paper | Code
β Mip-NeRF360: Project | Paper | Code
β Ref-NeRF: Project | Paper | Code
More: https://bit.ly/3qUgmgC
π7π€―1
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π₯Ά Lumos by #Nvidia: Relighting Portrait π₯Ά
πThe new SOTA in relighting without requiring a light stage
πReview https://bit.ly/3dCH9ej
πProject deepimagination.cc/Lumos
πPaper arxiv.org/pdf/2209.10510.pdf
πDemo http://imaginaire.cc/Lumos/
πThe new SOTA in relighting without requiring a light stage
πReview https://bit.ly/3dCH9ej
πProject deepimagination.cc/Lumos
πPaper arxiv.org/pdf/2209.10510.pdf
πDemo http://imaginaire.cc/Lumos/
β€11π1
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π SURF-GAN: NeRF - >StyleGAN π
π Editable portraits by injecting the NeRF's prior into StyleGAN
πReview https://bit.ly/3SohEw3
πProject jgkwak95.github.io/surfgan
πPaper arxiv.org/pdf/2207.10257.pdf
πCode github.com/jgkwak95/SURF-GAN
π Editable portraits by injecting the NeRF's prior into StyleGAN
πReview https://bit.ly/3SohEw3
πProject jgkwak95.github.io/surfgan
πPaper arxiv.org/pdf/2207.10257.pdf
πCode github.com/jgkwak95/SURF-GAN
π4β€2β€βπ₯1
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π₯#Google just announced "TensorStore"π₯
πNovel open-source C++ / #Python library for storage/manipulation of high-dim data
πReview https://bit.ly/3DLwbha
πProject https://bit.ly/3C4T2TR
πCode github.com/google/tensorstore
πNovel open-source C++ / #Python library for storage/manipulation of high-dim data
πReview https://bit.ly/3DLwbha
πProject https://bit.ly/3C4T2TR
πCode github.com/google/tensorstore
π₯14π2
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π¦ Motion Transformer for #selfdriving π¦
πThe 1st place solution for 2022 #waymo "motion prediction" challenge
πReview https://bit.ly/3f8G4LD
πPaper arxiv.org/pdf/2209.10033.pdf
πCode github.com/sshaoshuai/MTR
πThe 1st place solution for 2022 #waymo "motion prediction" challenge
πReview https://bit.ly/3f8G4LD
πPaper arxiv.org/pdf/2209.10033.pdf
πCode github.com/sshaoshuai/MTR
π₯17π3
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πΉ Image Synthesis @160+ FPS! πΉ
πSuper-fast, 3D-Aware Image Synthesis with Sparse Voxels -> up to 167 FPS!
πReview https://bit.ly/3r3ZNij
πPaper arxiv.org/pdf/2206.07695.pdf
πProject katjaschwarz.github.io/voxgraf
πSuper-fast, 3D-Aware Image Synthesis with Sparse Voxels -> up to 167 FPS!
πReview https://bit.ly/3r3ZNij
πPaper arxiv.org/pdf/2206.07695.pdf
πProject katjaschwarz.github.io/voxgraf
π3π€―2π₯1π―1
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π #Nvidia GET3D: #3D generative #AI π
πAI-based Textured 3D meshes with complex topology, rich geometry & hi-fi textures
πReview https://bit.ly/3SgnT5h
πCode github.com/nv-tlabs/GET3D
πProject nv-tlabs.github.io/GET3D/
πPaper nv-tlabs.github.io/GET3D/assets/paper.pdf
πAI-based Textured 3D meshes with complex topology, rich geometry & hi-fi textures
πReview https://bit.ly/3SgnT5h
πCode github.com/nv-tlabs/GET3D
πProject nv-tlabs.github.io/GET3D/
πPaper nv-tlabs.github.io/GET3D/assets/paper.pdf
β€βπ₯7π5
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π₯π₯ IDE-3D: source code is out! π₯π₯
πNovel, photorealistic, 3D-aware facial generator: source code just released!
πReview https://bit.ly/3BNrO2C
πProject mrtornado24.github.io/IDE-3D/
πCode github.com/MrTornado24/IDE-3D
πPaper arxiv.org/pdf/2205.15517.pdf
πNovel, photorealistic, 3D-aware facial generator: source code just released!
πReview https://bit.ly/3BNrO2C
πProject mrtornado24.github.io/IDE-3D/
πCode github.com/MrTornado24/IDE-3D
πPaper arxiv.org/pdf/2205.15517.pdf
π€―8π5π₯3π€©3
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π₯Diffusion Model of Neural Checkpointsπ₯
πConditional diffusion model on Millions of checkpoints of a given task/architecture π€―
πReview https://bit.ly/3SBR4Qb
πProject www.wpeebles.com/Gpt
πCode github.com/wpeebles/G.pt
πPaper arxiv.org/pdf/2209.12892.pdf
πConditional diffusion model on Millions of checkpoints of a given task/architecture π€―
πReview https://bit.ly/3SBR4Qb
πProject www.wpeebles.com/Gpt
πCode github.com/wpeebles/G.pt
πPaper arxiv.org/pdf/2209.12892.pdf
π€―5β€1
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π₯ Semantic VISOR dataset is out! π₯
πSegmenting hands / active objects in egocentric video (millions masks)
πReview https://bit.ly/3LOBLBv
πProject epic-kitchens.github.io/VISOR/
πPaper arxiv.org/pdf/2209.13064.pdf
πSegmenting hands / active objects in egocentric video (millions masks)
πReview https://bit.ly/3LOBLBv
πProject epic-kitchens.github.io/VISOR/
πPaper arxiv.org/pdf/2209.13064.pdf
π€―8π₯4π1
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π₯π₯ Olympic Games in 2028? π₯π₯
π In a few years, the fastest runner on earth will not be a human π₯Ά
πReview https://bit.ly/3Rme3O3
π In a few years, the fastest runner on earth will not be a human π₯Ά
πReview https://bit.ly/3Rme3O3
π±8π3π1