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🛵 ALPR via CTS-Matching 🛵
👉UIT unveils a neural approach (#YOLO5 + tracking + rotation) to improve the license plate recognition accuracy
😎Review https://t.ly/VP4BP
😎Paper arxiv.org/pdf/2307.11336.pdf
😎Code github.com/chequanghuy/Character-Time-series-Matching
👉UIT unveils a neural approach (#YOLO5 + tracking + rotation) to improve the license plate recognition accuracy
😎Review https://t.ly/VP4BP
😎Paper arxiv.org/pdf/2307.11336.pdf
😎Code github.com/chequanghuy/Character-Time-series-Matching
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🥬 Generative AI’s Next Frontiers 🥬
👉Hair simulation, 2D->3D animation, and much more. ~20 papers from #NVIDIA accepted into #SIGGRAPH2023
😎 Review https://t.ly/wgGin
👉Hair simulation, 2D->3D animation, and much more. ~20 papers from #NVIDIA accepted into #SIGGRAPH2023
😎 Review https://t.ly/wgGin
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🦀 simPLE: learning to grasp only with CAD 🦀
👉simPLE learns to pick, regrasp & place objects precisely, given only the object CAD model and no prior experience
😎Review https://t.ly/ab5pA
😎Paper arxiv.org/pdf/2307.13133.pdf
😎Project mcube.mit.edu/research/simPLE.html
👉simPLE learns to pick, regrasp & place objects precisely, given only the object CAD model and no prior experience
😎Review https://t.ly/ab5pA
😎Paper arxiv.org/pdf/2307.13133.pdf
😎Project mcube.mit.edu/research/simPLE.html
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🐧 Track Anything in HQ 🐧
👉Video multi-object segmenter (VMOS) and a mask refiner (MR) to track anything
😎Review https://t.ly/hAvF2
😎Paper arxiv.org/pdf/2307.13974.pdf
😎Code github.com/jiawen-zhu/HQTrack
👉Video multi-object segmenter (VMOS) and a mask refiner (MR) to track anything
😎Review https://t.ly/hAvF2
😎Paper arxiv.org/pdf/2307.13974.pdf
😎Code github.com/jiawen-zhu/HQTrack
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🥬Consensus-Adaptive RANSAC🥬
👉Novel RANSAC that learns to explore the parameter space via a novel attention layer
😎Review https://t.ly/eSLmD
😎Paper arxiv.org/pdf/2307.14030.pdf
😎Code github.com/cavalli1234/CA-RANSAC
👉Novel RANSAC that learns to explore the parameter space via a novel attention layer
😎Review https://t.ly/eSLmD
😎Paper arxiv.org/pdf/2307.14030.pdf
😎Code github.com/cavalli1234/CA-RANSAC
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🍡 DWPose: 2-stage Pose Distillation 🍡
👉 Tsinghua (+IDEA) unveils a novel two-stage pose Distillation for whole-body pose estimation.
😎Review https://t.ly/BSi20
😎Paper arxiv.org/pdf/2307.15880.pdf
😎Code github.com/IDEA-Research/DWPose
👉 Tsinghua (+IDEA) unveils a novel two-stage pose Distillation for whole-body pose estimation.
😎Review https://t.ly/BSi20
😎Paper arxiv.org/pdf/2307.15880.pdf
😎Code github.com/IDEA-Research/DWPose
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👗 Multimodal Neural Designer 👗
👉 Multimodal #AI that can generate novel fashion images conditioned on text, keypoints, and sketches
😎Review https://t.ly/zVk70
😎Paper arxiv.org/pdf/2304.02051.pdf
😎Code github.com/aimagelab/multimodal-garment-designer
👉 Multimodal #AI that can generate novel fashion images conditioned on text, keypoints, and sketches
😎Review https://t.ly/zVk70
😎Paper arxiv.org/pdf/2304.02051.pdf
😎Code github.com/aimagelab/multimodal-garment-designer
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📸 Computational Burst Photography in App 📸
👉#Google unveils a novel computational burst system to democratize the professional photography via smartphone
😎Review https://t.ly/5ibJX
😎Paper arxiv.org/pdf/2308.01379.pdf
😎Project https://motion-mode.github.io
👉#Google unveils a novel computational burst system to democratize the professional photography via smartphone
😎Review https://t.ly/5ibJX
😎Paper arxiv.org/pdf/2308.01379.pdf
😎Project https://motion-mode.github.io
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🎠Neural Closed-Loop Simulator🎠
👉A 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
😎Review https://t.ly/EcRLc
😎Paper arxiv.org/pdf/2308.01898.pdf
😎Project https://waabi.ai/unisim/
👉A 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
😎Review https://t.ly/EcRLc
😎Paper arxiv.org/pdf/2308.01898.pdf
😎Project https://waabi.ai/unisim/
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🙏 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 «🙏 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 :)»
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🪛 HANDAL: Real-World Manipulable Objects 🪛
👉 #Nvidia unveils HANDAL dataset: category-level object pose and affordance prediction
😎Review https://t.ly/MXZDI
😎Paper arxiv.org/pdf/2308.01477.pdf
😎Dataset wenbowen123.github.io/handaldataset
👉 #Nvidia unveils HANDAL dataset: category-level object pose and affordance prediction
😎Review https://t.ly/MXZDI
😎Paper arxiv.org/pdf/2308.01477.pdf
😎Dataset wenbowen123.github.io/handaldataset
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🎨 Interactive Neural Painting 🎨
👉 Novel AI-powered tool to help artists in completing their artworks
😎Review https://t.ly/ELUb0
😎Paper arxiv.org/pdf/2307.16441.pdf
😎Project helia95.github.io/inp-website
😎Supp helia95.github.io/inp-website/supp_mat.html
👉 Novel AI-powered tool to help artists in completing their artworks
😎Review https://t.ly/ELUb0
😎Paper arxiv.org/pdf/2307.16441.pdf
😎Project helia95.github.io/inp-website
😎Supp helia95.github.io/inp-website/supp_mat.html
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👩🚀 HD Avatar via Text & Pose 👩🚀
👉 Generating expressive #3D avatars from nothing but text descriptions & pose guidance
😎Review https://t.ly/wrSMH
😎Paper arxiv.org/pdf/2308.03610.pdf
😎Project avatarverse3d.github.io
👉 Generating expressive #3D avatars from nothing but text descriptions & pose guidance
😎Review https://t.ly/wrSMH
😎Paper arxiv.org/pdf/2308.03610.pdf
😎Project avatarverse3d.github.io
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🐘 Controllable Synthetic Data (extending Image-Net) 🐘
👉#META's PUG, a new generation of interactive environments for representation learning. Extending Image-Net!
😎Review https://t.ly/nCYs0
😎Paper arxiv.org/pdf/2308.03977.pdf
😎Project pug.metademolab.com
😎Code github.com/facebookresearch/PUG
👉#META's PUG, a new generation of interactive environments for representation learning. Extending Image-Net!
😎Review https://t.ly/nCYs0
😎Paper arxiv.org/pdf/2308.03977.pdf
😎Project pug.metademolab.com
😎Code github.com/facebookresearch/PUG
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AI with Papers - Artificial Intelligence & Deep Learning
🗽 Neuralangelo Digital Twins. INSANE🗽 👉 A novel framework from #Nvidia for Hi-Fi 3D Digital twins. 😎Review https://t.ly/rxoF4 😎Project research.nvidia.com/labs/dir/neuralangelo 😎Paper 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
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🌈 Tracking by Persistent Dynamic View Synthesis 🌈
👉Novel simultaneous addressing of dynamic scene novel-view synthesis + 6-DOF tracking of all dense scene elements
😎Review https://t.ly/Bc535
😎Paper arxiv.org/pdf/2308.09713.pdf
😎Project dynamic3dgaussians.github.io
😎Code github.com/JonathonLuiten/Dynamic3DGaussians
👉Novel simultaneous addressing of dynamic scene novel-view synthesis + 6-DOF tracking of all dense scene elements
😎Review https://t.ly/Bc535
😎Paper arxiv.org/pdf/2308.09713.pdf
😎Project dynamic3dgaussians.github.io
😎Code github.com/JonathonLuiten/Dynamic3DGaussians
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🛒 Digital Twins for AutoRetail Checkout 🛒
👉From #Nvidia a novel approach for using 3D assets for training 2D detection and tracking model in AutoRetail Checkout
😎Review https://t.ly/Ea7kt
😎Paper arxiv.org/pdf/2308.09708.pdf
😎Code github.com/yorkeyao/Automated-Retail-Checkout
👉From #Nvidia a novel approach for using 3D assets for training 2D detection and tracking model in AutoRetail Checkout
😎Review https://t.ly/Ea7kt
😎Paper arxiv.org/pdf/2308.09708.pdf
😎Code github.com/yorkeyao/Automated-Retail-Checkout
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🥎SportsMOT + MixSort = Sport MOT🥎
👉Nanjing just released a MOT dataset for sports scenes + the SOTA code/model for tracking (MixSort)
😎Review https://t.ly/NHUxL
😎Paper arxiv.org/pdf/2304.05170.pdf
😎Code github.com/MCG-NJU/MixSort
😎Project deeperaction.github.io/datasets/sportsmot.html
👉Nanjing just released a MOT dataset for sports scenes + the SOTA code/model for tracking (MixSort)
😎Review https://t.ly/NHUxL
😎Paper arxiv.org/pdf/2304.05170.pdf
😎Code github.com/MCG-NJU/MixSort
😎Project deeperaction.github.io/datasets/sportsmot.html
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⚡️Feature Matching at Light Speed⚡️
👉LightGlue is a lightweight feature matcher with high accuracy and blazing fast inference
😎Review https://t.ly/jkecX
😎Paper arxiv.org/pdf/2306.13643.pdf
😎Code github.com/cvg/LightGlue
👉LightGlue is a lightweight feature matcher with high accuracy and blazing fast inference
😎Review https://t.ly/jkecX
😎Paper arxiv.org/pdf/2306.13643.pdf
😎Code github.com/cvg/LightGlue
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🕹️ CoDeF: Video Content Deformation Fields 🕹️
👉CoDeF is a new type of video representation for video-editing tasks
😎Review https://t.ly/PIVl-
😎Paper arxiv.org/pdf/2308.07926.pdf
😎Project https://qiuyu96.github.io/CoDeF
😎Code https://github.com/qiuyu96/CoDeF
👉CoDeF is a new type of video representation for video-editing tasks
😎Review https://t.ly/PIVl-
😎Paper arxiv.org/pdf/2308.07926.pdf
😎Project https://qiuyu96.github.io/CoDeF
😎Code https://github.com/qiuyu96/CoDeF
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