AI with Papers - Artificial Intelligence & Deep Learning
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All the AI with papers. Every day fresh updates on Deep Learning, Machine Learning, and Computer Vision (with Papers).

Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/
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🏜Insane Neural Asset by #META 🏜

👉DiffRF: novel 3D radiance field synthesis based on denoising diffusion

😎Review https://bit.ly/3V5Daqo
😎Project sirwyver.github.io/DiffRF/
😎Paper arxiv.org/pdf/2212.01206.pdf
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🎸 RIFFUSION: #AI that sounds! 🎸

👉RIFFUSION: real-time music generation via spectrograms created with #stablediffusion

😎Review https://bit.ly/3GcOtcd
😎Project www.riffusion.com/about
😎App https://www.riffusion.com/
😎Code github.com/riffusion/riffusion-inference
😎Model huggingface.co/riffusion/riffusion-model-v1
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🪴 Rodin: 3D Avatars Using Diffusion 🪴

👉#Microsoft unveils a novel #3D diffusion for digital avatars as NeRF

😎Review https://bit.ly/3jcxeOX
😎Project 3d-avatar-diffusion.microsoft.com
😎Paper arxiv.org/pdf/2212.06135.pdf
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🔥 #AIwithPapers: we are ~5,5k 🔥

👉 I see you: everyone hot for #CHATGPT. But Computer Vision still loves you. We miss you all, don't break up with us 🧡

😈 Forward this post!
😈 Let's talk -> https://bit.ly/3v389IT
😈 Invite -> https://t.me/AI_DeepLearning
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🤯 Point·E: the "DALL·E" of 3D pts cloud 🤯

👉OpenAI opens Point·E: the "evolution" of DALL·E in the #3D point cloud domain

😎Review https://bit.ly/3I87PR9
😎Code github.com/openai/point-e
😎Paper arxiv.org/pdf/2212.08751.pdf
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🥑InstantAvatar: Avatar in 1 min.🥑

👉Avatars from monocular video in ONE minute (130x faster than SOTA)

😎Review https://bit.ly/3PNw1tJ
😎Paper arxiv.org/pdf/2212.10550.pdf
😎Project tijiang13.github.io/InstantAvatar
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🐬 DeepLSD: Neural Lines Detector 🐬

👉 DeepLSD: novel neural line detector in the wild. Paper, Code, and Models available

😎Review https://bit.ly/3WqONK2
😎Paper arxiv.org/pdf/2212.07766.pdf
😎Code github.com/cvg/deeplsd
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❄️ ClimateNeRF: Extreme Climate NeRF ❄️

👉NeRF-based realistic climate change simulations for disaster forecasting

😎Review https://bit.ly/3vhqdz6
😎Paper arxiv.org/pdf/2211.13226.pdf
😎Project https://climatenerf.github.io
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☃️ Neural Smooth Video Composition ☃️

👉The novel SOTA in neural video composition. From a few frames to infinite!

😎Review https://bit.ly/3hRyaIe
😎Code github.com/genforce/StyleSV
😎Paper arxiv.org/pdf/2212.07413.pdf
😎Project genforce.github.io/StyleSV/
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🎆 One-Shot Video Generation 🎆

👉Tune-A-Video: One-Shot Video Generation with no training pain!

😎Review https://bit.ly/3hX47il
😎Paper arxiv.org/pdf/2212.11565.pdf
😎Project https://tuneavideo.github.io/
😎Code github.com/showlab/Tune-A-Video
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🍯 Interpretable Shape Programs 🍯

👉GeoCode: #3D shape synthesis via intuitively editable parameters

😎Review https://bit.ly/3PYgc3o
😎Paper arxiv.org/pdf/2212.11715.pdf
😎Code github.com/threedle/GeoCode
😎Project threedle.github.io/GeoCode
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🎇 Real-Time NeRF+SLAM 🎇

👉Novel geometric/photometric 3D mapping pipeline powered by NeRF+SLAM

😎Review https://bit.ly/3G6xEOO
😎Paper arxiv.org/pdf/2210.13641.pdf
😎Code github.com/ToniRV/NeRF-SLAM
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💡MetaPortrait: ID-preserving talking head💡

👉USTC unveils a novel ID-preserving talking head generation framework

😎Review https://bit.ly/3jyVWsW
😎Paper arxiv.org/pdf/2212.08062.pdf
😎Project https://meta-portrait.github.io
😎Code github.com/Meta-Portrait/MetaPortrait
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⚛️ Event-based vehicle tracking ⚛️

👉Novel event-based vehicle detection/tracking framework. Dataset included!

😎Review https://bit.ly/3vzxWJ7
😎Paper
arxiv.org/ftp/arxiv/papers/2212/2212.14289.pdf
😎Dataset
sar-lab.net/event-based-vehicle-detection-and-tracking-dataset
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⚠️ ALERT: #PyTorch COMPROMISED ⚠️

[EDIT: THE ALERT IS NOT CONFIRMED, IT COULD BE JUST A BUG]

👉PyTorch-nightly packages installed via pip compromised with malicious binary 🦠

😎More https://bit.ly/3WEm5p1
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🍏 MUSE: T2I Generative Transformers 🍏

👉Google unveils the new SOTA (faster and better) for text-to-image generation

😎Review https://bit.ly/3CeEu3B
😎Paper arxiv.org/pdf/2301.00704.pdf
😎Project muse-model.github.io
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🔢 #AI Advanced Math Reasoning 🔢

👉#Meta unveils HTPS: SOTA transformer-based theorem prover.

😎Review https://bit.ly/3CoUsrP
😎Paper arxiv.org/pdf/2205.11491.pdf
😎Blog ai.facebook.com/blog/ai-math-theorem-proving
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