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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🐚 Diffusion Game Engine 🐚

👉#Google unveils GameNGen: the first game engine powered entirely by a neural #AI that enables real-time interaction with a complex environment over long trajectories at HQ. No code announced but I love it 💙

👉Review https://t.ly/_WR5z
👉Paper https://lnkd.in/dZqgiqb9
👉Project https://lnkd.in/dJUd2Fr6
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ðŸŦ’ Omni Urban Scene Reconstruction ðŸŦ’

👉OmniRe is novel holistic approach for efficiently reconstructing HD dynamic urban scenes from on-device logs. It's able to create the simulation of reconstructed scenarios with actors in real-time (~60 Hz). Code released💙

👉Review https://t.ly/SXVPa
👉Paper arxiv.org/pdf/2408.16760
👉Project ziyc.github.io/omnire/
👉Code github.com/ziyc/drivestudio
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💄Interactive Drag-based Editing💄

👉CSE unveils InstantDrag: novel pipeline designed to enhance editing interactivity and speed, taking only an image and a drag instruction as input. Source Code announced, coming💙

👉Review https://t.ly/hy6SL
👉Paper arxiv.org/pdf/2409.08857
👉Project joonghyuk.com/instantdrag-web/
👉Code github.com/alex4727/InstantDrag
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🌭Hand-Object interaction Pretraining🌭

👉Berkeley unveils HOP, a novel approach to learn general robot manipulation priors from 3D hand-object interaction trajectories.

👉Review https://t.ly/FLqvJ
👉Paper https://arxiv.org/pdf/2409.08273
👉Project https://hgaurav2k.github.io/hop/
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ðŸ§ļMotion Instruction Fine-TuningðŸ§ļ

👉MotIF is a novel method that fine-tunes pre-trained VLMs to equip the capability to distinguish nuanced robotic motions with different shapes and semantic groundings. A work by MIT, Stanford, and CMU. Source Code announced, coming💙

👉Review https://t.ly/iJ2UY
👉Paper https://arxiv.org/pdf/2409.10683
👉Project https://motif-1k.github.io/
👉Code coming
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âš― SoccerNet 2024 Results âš―

👉SoccerNet is the annual video understanding challenge for football. These challenges aim to advance research across multiple themes in football. The 2024 results are out!

👉Review https://t.ly/DUPgx
👉Paper arxiv.org/pdf/2409.10587
👉Repo github.com/SoccerNet
👉Project www.soccer-net.org/
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🌏 JoyHallo: Mandarin Digital Human 🌏

👉JD Health faced the challenges of audio-driven video generation in Mandarin, a task complicated by the language’s intricate lip movements and the scarcity of HQ datasets. Impressive results (-> audio ON). Code Models available💙

👉Review https://t.ly/5NGDh
👉Paper arxiv.org/pdf/2409.13268
👉Project jdh-algo.github.io/JoyHallo/
👉Code github.com/jdh-algo/JoyHallo
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ðŸŽĒ Robo-quadruped ParkourðŸŽĒ

👉LAAS-CNRS unveils a novel RL approach to perform agile skills that are reminiscent of parkour, such as walking, climbing high steps, leaping over gaps, and crawling under obstacles. Data and Code available💙

👉Review https://t.ly/-6VRm
👉Paper arxiv.org/pdf/2409.13678
👉Project gepetto.github.io/SoloParkour/
👉Code github.com/Gepetto/SoloParkour
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ðŸĐ° Dressed Humans in the wild ðŸĐ°

👉ETH (+ #Microsoft ) ReLoo: novel 3D-HQ reconstruction of humans dressed in loose garments from mono in-the-wild clips. No prior assumptions about the garments. Source Code announced, coming 💙

👉Review https://t.ly/evgmN
👉Paper arxiv.org/pdf/2409.15269
👉Project moygcc.github.io/ReLoo/
👉Code github.com/eth-ait/ReLoo
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ðŸŒū New SOTA Edge Detection ðŸŒū

👉CUP (+ ESPOCH) unveils the new SOTA for Edge Detection (NBED); superior performance consistently across multiple benchmarks, even compared with huge computational cost and complex training models. Source Code released💙

👉Review https://t.ly/zUMcS
👉Paper arxiv.org/pdf/2409.14976
👉Code github.com/Li-yachuan/NBED
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ðŸ‘Đ‍ðŸĶ° SOTA Gaussian Haircut ðŸ‘Đ‍ðŸĶ°

👉ETH et. al unveils Gaussian Haircut, the new SOTA in hair reconstruction via dual representation (classic + 3D Gaussian). Code and Model announced💙

👉Review https://t.ly/aiOjq
👉Paper arxiv.org/pdf/2409.14778
👉Project https://lnkd.in/dFRm2ycb
👉Repo https://lnkd.in/d5NWNkb5
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🍇SPARK: Real-time Face Capture🍇

👉Technicolor Group unveils SPARK, a novel high-precision 3D face capture via collection of unconstrained videos of a subject as prior information. New SOTA able to handle unseen pose, expression and lighting. Impressive results. Code & Model announced💙

👉Review https://t.ly/rZOgp
👉Paper arxiv.org/pdf/2409.07984
👉Project kelianb.github.io/SPARK/
👉Repo github.com/KelianB/SPARK/
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ðŸĶī One-Image Object Detection ðŸĶī

👉Delft University (+Hensoldt Optronics) introduces OSSA, a novel unsupervised domain adaptation method for object detection that utilizes a single, unlabeled target image to approximate the target domain style. Code released💙

👉Review https://t.ly/-li2G
👉Paper arxiv.org/pdf/2410.00900
👉Code github.com/RobinGerster7/OSSA
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ðŸ›ģïļ EVER Ellipsoid Rendering ðŸ›ģïļ

👉UCSD & Google present EVER, a novel method for real-time differentiable emission-only volume rendering. Unlike 3DGS it does not suffer from popping artifacts and view dependent density, achieving ∞30 FPS at 720p on #NVIDIA RTX4090.

👉Review https://t.ly/zAfGU
👉Paper arxiv.org/pdf/2410.01804
👉Project half-potato.gitlab.io/posts/ever/
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ðŸ”Ĩ "Deep Gen-AI" Full Course ðŸ”Ĩ

👉A fresh course from Stanford about the probabilistic foundations and algorithms for deep generative models. A novel overview about the evolution of the genAI in #computervision, language and more...

👉Review https://t.ly/ylBxq
👉Course https://lnkd.in/dMKH9gNe
👉Lectures https://lnkd.in/d_uwDvT6
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🐏 EFM3D: 3D Ego-Foundation 🐏

👉#META presents EFM3D, the first benchmark for 3D object detection and surface regression on HQ annotated egocentric data of Project Aria. Datasets & Code released💙

👉Review https://t.ly/cDJv6
👉Paper arxiv.org/pdf/2406.10224
👉Project www.projectaria.com/datasets/aeo/
👉Repo github.com/facebookresearch/efm3d
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ðŸĨĶGaussian Splatting VTONðŸĨĶ

👉GS-VTON is a novel image-prompted 3D-VTON which, by leveraging 3DGS as the 3D representation, enables the transfer of pre-trained knowledge from 2D VTON models to 3D while improving cross-view consistency. Code announced💙

👉Review https://t.ly/sTPbW
👉Paper arxiv.org/pdf/2410.05259
👉Project yukangcao.github.io/GS-VTON/
👉Repo github.com/yukangcao/GS-VTON
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ðŸ’ĄDiffusion Models RelightingðŸ’Ą

👉#Netflix unveils DifFRelight, a novel free-viewpoint facial relighting via diffusion model. Precise lighting control, high-fidelity relit facial images from flat-lit inputs.

👉Review https://t.ly/fliXU
👉Paper arxiv.org/pdf/2410.08188
👉Project www.eyelinestudios.com/research/diffrelight.html
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ðŸĨŽPOKEFLEX: Soft Object DatasetðŸĨŽ

👉PokeFlex from ETH is a dataset that includes 3D textured meshes, point clouds, RGB & depth maps of deformable objects. Pretrained models & dataset announced💙

👉Review https://t.ly/GXggP
👉Paper arxiv.org/pdf/2410.07688
👉Project https://lnkd.in/duv-jS7a
👉Repo
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ðŸ”Ĩ DEPTH ANY VIDEO is out! ðŸ”Ĩ

👉DAV is a novel foundation model for image/video depth estimation.The new SOTA for accuracy & consistency, up to 150 FPS!

👉Review https://t.ly/CjSz2
👉Paper arxiv.org/pdf/2410.10815
👉Project depthanyvideo.github.io/
👉Code github.com/Nightmare-n/DepthAnyVideo
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