AI with Papers - Artificial Intelligence & Deep Learning
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All the AI with papers. Every day fresh updates about #DeepLearning, #MachineLearning, LLMs and #ComputerVision

Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/

#artificialintelligence #machinelearning #ml #AI
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๐ŸฆฉPhenaki: Text-to(LOOONG)Video generation๐Ÿฆฉ

๐Ÿ‘‰Phenaki is an #AI capable of realistic long video synthesis, given a sequence of textual open prompts

๐Ÿ˜ŽReview https://bit.ly/3RwUvXx
๐Ÿ˜ŽProject phenaki.video/index.h
๐Ÿ˜ŽPaper openreview.net/pdf?id=vOEXS39nOF
๐Ÿ”ฅ7โค3๐Ÿ‘1
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๐Ÿ”ฅ VToonify: Neural Portrait Style Transfer ๐Ÿ”ฅ

๐Ÿ‘‰VToonify for portrait style transfer. Powered by DualStyleGAN backbone, now with #stablediffusion!

๐Ÿ˜ŽReview https://bit.ly/3M9wgNP
๐Ÿ˜ŽDemo https://t.co/8gXzF3IrpB
๐Ÿ˜ŽPaper arxiv.org/pdf/2209.11224.pdf
๐Ÿ˜ŽProject mmlab-ntu.com/project/vtoonify
๐Ÿ˜ŽCode github.com/williamyang1991/VToonify
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๐Ÿข Stable Diffusion for #Pokemon ๐Ÿข

๐Ÿ‘‰Fine-tuning the stable diffusion to create a text-to-pokemon generation model

๐Ÿ˜ŽReview https://bit.ly/3C9qBTw
๐Ÿ˜ŽTutorial https://lambdalabs.com/blog/how-to-fine-tune-stable-diffusion-how-we-made-the-text-to-pokemon-model-at-lambda/
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๐Ÿ”ฅ Imagen Video by #Google. SICK! ๐Ÿ”ฅ

๐Ÿ‘‰Novel text-conditional video generation via cascade of video diffusion models ๐Ÿคฏ

๐Ÿ˜ŽReview https://bit.ly/3SH2TVH
๐Ÿ˜ŽProject imagen.research.google/video/
๐Ÿ˜ŽPaper imagen.research.google/video/paper.pdf
๐Ÿคฏ20๐Ÿ”ฅ7๐Ÿ‘1
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๐Ÿ”ฅ Human MDM: source code is out! ๐Ÿ”ฅ

๐Ÿ‘‰A classifier-free diffusion-based generative model for human motion domain

๐Ÿ˜ŽReview https://bit.ly/3rFhR2G
๐Ÿ˜ŽProject guytevet.github.io/mdm-page
๐Ÿ˜ŽPaper arxiv.org/pdf/2209.14916.pdf
๐Ÿ˜ŽCode github.com/GuyTevet/motion-diffusion-model
๐Ÿ”ฅ6๐Ÿ‘1
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โš›๏ธSOTA ALERT! Particles Tracking โš›๏ธ

๐Ÿ‘‰The new SOTA in video particles tracking. "Old school" taste, with neural flavor ๐Ÿงก

๐Ÿ˜ŽReview https://bit.ly/3CaU5Ai
๐Ÿ˜ŽProject particle-video-revisited.github.io/
๐Ÿ˜ŽPaper arxiv.org/pdf/2204.04153.pdf
๐Ÿ˜ŽCode github.com/aharley/pips
๐Ÿ‘7๐Ÿฅฐ4๐Ÿ”ฅ1
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๐Ÿ”ฅ #AIwithPapers: we are 4,500+! ๐Ÿ”ฅ

๐Ÿ’™๐Ÿ’› Someone put the smiling ๐Ÿ’ฉ under a few recent posts. But I still love you! ๐Ÿ’™๐Ÿ’›

๐Ÿ˜ˆ Invite your friends -> https://t.iss.one/AI_DeepLearning
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๐Ÿ‹ Long Video via Transformers ๐Ÿ‹

๐Ÿ‘‰TECO is a vector-quantized latent dynamics prediction for long video

๐Ÿ˜ŽReview https://bit.ly/3Ch0tWD
๐Ÿ˜ŽProject wilson1yan.github.io/teco/
๐Ÿ˜ŽPaper arxiv.org/pdf/2210.02396.pdf
๐Ÿ˜ŽCode github.com/wilson1yan/teco
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๐Ÿ”ฅSIMPLI: ligh novel-view synthesis๐Ÿ”ฅ

๐Ÿ‘‰Lightweight novel-view synthesis by #Samsung for arbitrary forward-facing scenes

๐Ÿ˜ŽReview https://bit.ly/3CivSYZ
๐Ÿ˜ŽProject samsunglabs.github.io/MLI
๐Ÿ˜ŽCode github.com/SamsungLabs/MLI
๐Ÿ˜ŽPaper samsunglabs.github.io/MLI/paper/paper.pdf
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๐Ÿฅ EVA3D: new SOTA in #3D humans ๐Ÿฅ

๐Ÿ‘‰EVA3D: new SOTA for unconditional NeRF-human generation from 2D only

๐Ÿ˜ŽReview https://bit.ly/3Th9qX7
๐Ÿ˜ŽCode github.com/hongfz16/EVA3D
๐Ÿ˜ŽPaper arxiv.org/pdf/2210.04888.pdf
๐Ÿ˜ŽProject hongfz16.github.io/projects/EVA3D.html
๐Ÿ”ฅ14๐Ÿ‘2
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๐Ÿ f-DM: Diffusion Models by Apple ๐Ÿ

๐Ÿ‘‰Spectacular work by #Apple on DMs: HQ generation with better efficiency and semantic

๐Ÿ˜ŽReview https://bit.ly/3Tils2u
๐Ÿ˜ŽProject https://jiataogu.me/fdm/
๐Ÿ˜ŽPaper arxiv.org/pdf/2210.04955.pdf
โค10๐Ÿ˜ฑ2๐Ÿ‘1
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๐Ÿ…GENIE by #Nvidia -> Faster Generation๐Ÿ…

๐Ÿ‘‰Higher-Order Denoising Diffusion Solvers for faster and better synthesis

๐Ÿ˜ŽReview https://bit.ly/3CRjtwr
๐Ÿ˜ŽProject nv-tlabs.github.io/GENIE/
๐Ÿ˜ŽPaper arxiv.org/pdf/2210.05475.pdf
๐Ÿ˜ŽCode github.com/nv-tlabs/GENIE
๐Ÿ”ฅ10๐Ÿ‘4
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๐Ÿฅฌ "Perception Test" by #DeepMind ๐Ÿฅฌ

๐Ÿ‘‰Huge dataset with obj & point tracks, temporal sounds, multiple & grounded vQA

๐Ÿ˜ŽReview https://bit.ly/3Vqh96Q
๐Ÿ˜ŽDataset github.com/deepmind/perception_test
๐Ÿ˜ŽProject www.deepmind.com/blog/measuring-perception-in-ai-models
๐Ÿ‘15๐Ÿ”ฅ4๐Ÿ˜ฑ3
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๐Ÿ”ฅ Matterport 3D Semantics Dataset ๐Ÿ”ฅ

๐Ÿ‘‰#Meta opens HM3DSEM, the largest #3D real-world dataset with dense semantic

๐Ÿ˜ŽReview https://bit.ly/3yF4W4G
๐Ÿ˜ŽPaper arxiv.org/pdf/2210.05633.pdf
๐Ÿ˜ŽProject aihabitat.org/datasets/hm3d-semantics
๐Ÿ˜ŽData github.com/matterport/habitat-matterport-3dresearch
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๐Ÿฆ‘ Instant Map-free Relocalization ๐Ÿฆ‘

๐Ÿ‘‰#Niantic unveils a novel instant, metric scaled re-localization with one single photo

๐Ÿ˜ŽReview https://bit.ly/3S1Gdyh
๐Ÿ˜ŽPaper arxiv.org/pdf/2210.05494.pdf
๐Ÿ˜ŽProject research.nianticlabs.com/mapfree-reloc-benchmark
๐Ÿ˜ŽData research.nianticlabs.com/mapfree-reloc-benchmark/dataset
๐Ÿ”ฅ13๐Ÿ‘2
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๐Ÿงฎ Novel DM for 3D Shapes by #Nvidia ๐Ÿงฎ

๐Ÿ‘‰Hierarchical Latent Point Diffusion Model (LION) for 3D shape generation

๐Ÿ˜ŽReview https://bit.ly/3yDhZ6I
๐Ÿ˜ŽPaper arxiv.org/pdf/2210.06978.pdf
๐Ÿ˜ŽProject https://nv-tlabs.github.io/LION/
๐Ÿ˜ŽCode(soon) github.com/nv-tlabs/LION
โค11๐Ÿ˜ฑ2๐Ÿ”ฅ1
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๐Ÿชฒ#6D estimation fully in the wild๐Ÿชฒ

๐Ÿ‘‰First ever self-supervised 6D pose estimation training in the wild

๐Ÿ˜ŽReview https://bit.ly/3yHdHuS
๐Ÿ˜ŽPaper arxiv.org/pdf/2210.07199.pdf
๐Ÿ˜ŽProject kywind.github.io/self-pose
๐Ÿ˜ŽCode (soon)
๐Ÿ‘15๐Ÿคฏ8๐Ÿ˜ฑ4
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โ›ฝ Stable Diffusion in #Blender โ›ฝ

๐Ÿ‘‰Render with SuperPowers: novel scene render via text prompt

๐Ÿ˜ŽReview https://bit.ly/3s1mEeN
๐Ÿ˜ŽCode github.com/benrugg/AI-Render
๐Ÿคฏ8๐Ÿ‘5โค2
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โšฝMarkerless Body-Object Interactionโšฝ

๐Ÿ‘‰Novel whole-bodies/objects interaction method from multi-view RGB-D data

๐Ÿ˜ŽReview https://bit.ly/3yO56GY
๐Ÿ˜ŽData intercap.is.tue.mpg.de/login.php
๐Ÿ˜ŽProject https://intercap.is.tue.mpg.de
๐Ÿ˜ŽCode github.com/YinghaoHuang91
๐Ÿ˜ŽPaper intercap.is.tue.mpg.de/media/upload/main.pdf
๐Ÿ”ฅ6๐Ÿ‘2๐Ÿพ1
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๐Ÿ”ฅ Dressing Avatars by #META ๐Ÿ”ฅ

๐Ÿ‘‰Novel deep photorealistic appearance method for physically-simulated clothing in #metaverse

๐Ÿ˜ŽReview https://bit.ly/3yRBW9Y
๐Ÿ˜ŽPaper arxiv.org/pdf/2206.15470.pdf
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