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π‘ DWPose: 2-stage Pose Distillation π‘
π Tsinghua (+IDEA) unveils a novel two-stage pose Distillation for whole-body pose estimation.
πReview https://t.ly/BSi20
πPaper arxiv.org/pdf/2307.15880.pdf
πCode github.com/IDEA-Research/DWPose
π Tsinghua (+IDEA) unveils a novel two-stage pose Distillation for whole-body pose estimation.
πReview https://t.ly/BSi20
πPaper arxiv.org/pdf/2307.15880.pdf
πCode github.com/IDEA-Research/DWPose
π€―7β€2π1π₯1π€©1
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π Multimodal Neural Designer π
π Multimodal #AI that can generate novel fashion images conditioned on text, keypoints, and sketches
πReview https://t.ly/zVk70
πPaper arxiv.org/pdf/2304.02051.pdf
πCode github.com/aimagelab/multimodal-garment-designer
π Multimodal #AI that can generate novel fashion images conditioned on text, keypoints, and sketches
πReview https://t.ly/zVk70
πPaper arxiv.org/pdf/2304.02051.pdf
πCode github.com/aimagelab/multimodal-garment-designer
π₯°6β€4π€©3π₯2β‘1
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πΈ Computational Burst Photography in App πΈ
π#Google unveils a novel computational burst system to democratize the professional photography via smartphone
πReview https://t.ly/5ibJX
πPaper arxiv.org/pdf/2308.01379.pdf
πProject https://motion-mode.github.io
π#Google unveils a novel computational burst system to democratize the professional photography via smartphone
πReview https://t.ly/5ibJX
πPaper arxiv.org/pdf/2308.01379.pdf
πProject https://motion-mode.github.io
π₯6π₯°3π2π€©1
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π Neural Closed-Loop Simulatorπ
πA neural sensor simulator that takes a single recorded log captured by a sensor-equipped vehicle and converts it into a realistic closed-loop multi-sensor simulation
πReview https://t.ly/EcRLc
πPaper arxiv.org/pdf/2308.01898.pdf
πProject https://waabi.ai/unisim/
πA neural sensor simulator that takes a single recorded log captured by a sensor-equipped vehicle and converts it into a realistic closed-loop multi-sensor simulation
πReview https://t.ly/EcRLc
πPaper arxiv.org/pdf/2308.01898.pdf
πProject https://waabi.ai/unisim/
π€―8π€©3β€2π2π₯1π1
π A quick poll for helping me in improving the quality of the contents about #computervision.
Please give me a feedback here: https://t.ly/qXb4C
Thanks :)
Please give me a feedback here: https://t.ly/qXb4C
Thanks :)
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AI with Papers - Artificial Intelligence & Deep Learning pinned Β«π A quick poll for helping me in improving the quality of the contents about #computervision. Please give me a feedback here: https://t.ly/qXb4C Thanks :)Β»
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πͺ HANDAL: Real-World Manipulable Objects πͺ
π #Nvidia unveils HANDAL dataset: category-level object pose and affordance prediction
πReview https://t.ly/MXZDI
πPaper arxiv.org/pdf/2308.01477.pdf
πDataset wenbowen123.github.io/handaldataset
π #Nvidia unveils HANDAL dataset: category-level object pose and affordance prediction
πReview https://t.ly/MXZDI
πPaper arxiv.org/pdf/2308.01477.pdf
πDataset wenbowen123.github.io/handaldataset
π8π₯3β€1π€©1
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π¨ Interactive Neural Painting π¨
π Novel AI-powered tool to help artists in completing their artworks
πReview https://t.ly/ELUb0
πPaper arxiv.org/pdf/2307.16441.pdf
πProject helia95.github.io/inp-website
πSupp helia95.github.io/inp-website/supp_mat.html
π Novel AI-powered tool to help artists in completing their artworks
πReview https://t.ly/ELUb0
πPaper arxiv.org/pdf/2307.16441.pdf
πProject helia95.github.io/inp-website
πSupp helia95.github.io/inp-website/supp_mat.html
π€©4π€―2β€1π1π±1
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π©βπ HD Avatar via Text & Pose π©βπ
π Generating expressive #3D avatars from nothing but text descriptions & pose guidance
πReview https://t.ly/wrSMH
πPaper arxiv.org/pdf/2308.03610.pdf
πProject avatarverse3d.github.io
π Generating expressive #3D avatars from nothing but text descriptions & pose guidance
πReview https://t.ly/wrSMH
πPaper arxiv.org/pdf/2308.03610.pdf
πProject avatarverse3d.github.io
β€7π₯°4π1π€―1
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π Controllable Synthetic Data (extending Image-Net) π
π#META's PUG, a new generation of interactive environments for representation learning. Extending Image-Net!
πReview https://t.ly/nCYs0
πPaper arxiv.org/pdf/2308.03977.pdf
πProject pug.metademolab.com
πCode github.com/facebookresearch/PUG
π#META's PUG, a new generation of interactive environments for representation learning. Extending Image-Net!
πReview https://t.ly/nCYs0
πPaper arxiv.org/pdf/2308.03977.pdf
πProject pug.metademolab.com
πCode github.com/facebookresearch/PUG
π₯4β€2π1π€©1
AI with Papers - Artificial Intelligence & Deep Learning
π½ Neuralangelo Digital Twins. INSANEπ½ π A novel framework from #Nvidia for Hi-Fi 3D Digital twins. πReview https://t.ly/rxoF4 πProject research.nvidia.com/labs/dir/neuralangelo πPaper research.nvidia.com/labs/dir/neuralangelo/paper.pdf
GitHub
GitHub - NVlabs/neuralangelo: Official implementation of "Neuralangelo: High-Fidelity Neural Surface Reconstruction" (CVPR 2023)
Official implementation of "Neuralangelo: High-Fidelity Neural Surface Reconstruction" (CVPR 2023) - NVlabs/neuralangelo
π₯11π6β€2π±1
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π Tracking by Persistent Dynamic View Synthesis π
πNovel simultaneous addressing of dynamic scene novel-view synthesis + 6-DOF tracking of all dense scene elements
πReview https://t.ly/Bc535
πPaper arxiv.org/pdf/2308.09713.pdf
πProject dynamic3dgaussians.github.io
πCode github.com/JonathonLuiten/Dynamic3DGaussians
πNovel simultaneous addressing of dynamic scene novel-view synthesis + 6-DOF tracking of all dense scene elements
πReview https://t.ly/Bc535
πPaper arxiv.org/pdf/2308.09713.pdf
πProject dynamic3dgaussians.github.io
πCode github.com/JonathonLuiten/Dynamic3DGaussians
π€―10π₯3π±1
π Digital Twins for AutoRetail Checkout π
πFrom #Nvidia a novel approach for using 3D assets for training 2D detection and tracking model in AutoRetail Checkout
πReview https://t.ly/Ea7kt
πPaper arxiv.org/pdf/2308.09708.pdf
πCode github.com/yorkeyao/Automated-Retail-Checkout
πFrom #Nvidia a novel approach for using 3D assets for training 2D detection and tracking model in AutoRetail Checkout
πReview https://t.ly/Ea7kt
πPaper arxiv.org/pdf/2308.09708.pdf
πCode github.com/yorkeyao/Automated-Retail-Checkout
π₯2π₯°2π±2
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π₯SportsMOT + MixSort = Sport MOTπ₯
πNanjing just released a MOT dataset for sports scenes + the SOTA code/model for tracking (MixSort)
πReview https://t.ly/NHUxL
πPaper arxiv.org/pdf/2304.05170.pdf
πCode github.com/MCG-NJU/MixSort
πProject deeperaction.github.io/datasets/sportsmot.html
πNanjing just released a MOT dataset for sports scenes + the SOTA code/model for tracking (MixSort)
πReview https://t.ly/NHUxL
πPaper arxiv.org/pdf/2304.05170.pdf
πCode github.com/MCG-NJU/MixSort
πProject deeperaction.github.io/datasets/sportsmot.html
π₯12π2π€―2β€1π€©1
β‘οΈFeature Matching at Light Speedβ‘οΈ
πLightGlue is a lightweight feature matcher with high accuracy and blazing fast inference
πReview https://t.ly/jkecX
πPaper arxiv.org/pdf/2306.13643.pdf
πCode github.com/cvg/LightGlue
πLightGlue is a lightweight feature matcher with high accuracy and blazing fast inference
πReview https://t.ly/jkecX
πPaper arxiv.org/pdf/2306.13643.pdf
πCode github.com/cvg/LightGlue
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πΉοΈ CoDeF: Video Content Deformation Fields πΉοΈ
πCoDeF is a new type of video representation for video-editing tasks
πReview https://t.ly/PIVl-
πPaper arxiv.org/pdf/2308.07926.pdf
πProject https://qiuyu96.github.io/CoDeF
πCode https://github.com/qiuyu96/CoDeF
πCoDeF is a new type of video representation for video-editing tasks
πReview https://t.ly/PIVl-
πPaper arxiv.org/pdf/2308.07926.pdf
πProject https://qiuyu96.github.io/CoDeF
πCode https://github.com/qiuyu96/CoDeF
β€18π₯4π2π₯°1π€―1π±1
Hello everybody,
a lot of you asked me to open the comments to better enjoy the posts. I want to follow your suggestion, hope you will enjoy this new mood!
π₯ NO SPAM
π₯ NO COMMERCIAL
π₯ NO UNRESPECTFUL MESSAGEs
π§‘JUST AI & SCIENCE
β οΈ BAN AT THE FIRST VIOLATION β οΈ
a lot of you asked me to open the comments to better enjoy the posts. I want to follow your suggestion, hope you will enjoy this new mood!
π₯ NO SPAM
π₯ NO COMMERCIAL
π₯ NO UNRESPECTFUL MESSAGEs
π§‘JUST AI & SCIENCE
β οΈ BAN AT THE FIRST VIOLATION β οΈ
β€44π28π₯6π1π€―1πΎ1
AI with Papers - Artificial Intelligence & Deep Learning pinned Β«Hello everybody, a lot of you asked me to open the comments to better enjoy the posts. I want to follow your suggestion, hope you will enjoy this new mood! π₯ NO SPAM π₯ NO COMMERCIAL π₯ NO UNRESPECTFUL MESSAGEs π§‘JUST AI & SCIENCE β οΈ BAN AT THE FIRSTβ¦Β»
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π¦ Instance-Level Semantics of Cells π¦
πTYC: novel dataset for understanding instance-level semantics & motions of cells in microstructures
πReview https://t.ly/y-4VZ
πPaper arxiv.org/pdf/2308.12116.pdf
πProject christophreich1996.github.io/tyc_dataset/
πCode github.com/ChristophReich1996/TYC-Dataset
πData tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3930
πTYC: novel dataset for understanding instance-level semantics & motions of cells in microstructures
πReview https://t.ly/y-4VZ
πPaper arxiv.org/pdf/2308.12116.pdf
πProject christophreich1996.github.io/tyc_dataset/
πCode github.com/ChristophReich1996/TYC-Dataset
πData tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3930
π8π₯3β€1β‘1π€―1
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π΅POCO: 3D HPS + Confidenceπ΅
π Novel framework for HPS: #3D human body + confidence in a single feed-forward pass
πReview https://t.ly/cDePe
πPaper arxiv.org/pdf/2308.12965.pdf
πProject https://poco.is.tue.mpg.de
π Novel framework for HPS: #3D human body + confidence in a single feed-forward pass
πReview https://t.ly/cDePe
πPaper arxiv.org/pdf/2308.12965.pdf
πProject https://poco.is.tue.mpg.de
π₯5π3β€2π€―1π±1