AI with Papers - Artificial Intelligence & Deep Learning – Telegram
AI with Papers - Artificial Intelligence & Deep Learning
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All the AI with papers. Every day fresh updates about #DeepLearning #MachineLearning #LLM & #ComputerVision

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

#AI #chatGPT
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🍏#Nvidia Dynamic Pose 🍏

👉Nvidia unveils DynPose-100K, the largest dataset of dynamic Internet videos annotated with camera poses. Dataset released under Nvidia license💙

👉Review https://t.ly/wrcb0
👉Paper https://lnkd.in/dycGjAyy
👉Project https://lnkd.in/dDZ2Ej_Q
🤗Data https://lnkd.in/d8yUSB7m
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🔥 S3MOT: SOTA 3D MOT 🔥

👉S3MOT: Selective-State-Space model-based MOT that efficiently infers 3D motion and object associations from 2D images through three core components. New SOTA on KITTI with 76.86 HOTA at 31 FPS! Code & Weights to be released under MIT license💙

👉Review https://t.ly/H_JPv
👉Paper https://arxiv.org/pdf/2504.18068
👉Repo https://github.com/bytepioneerX/s3mot
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🔥 Diffusion Model <-> Depth 🔥

👉ETH & CMU on how to turn a single-image latent diffusion model (LDM) into the SOTA video depth estimator: video depth without video models. Repo released under Apache 2.0 and HF demo available💙

👉Review https://t.ly/sP9ma
👉Paper arxiv.org/pdf/2411.19189
👉Project rollingdepth.github.io/
👉Repo github.com/prs-eth/rollingdepth
🤗Demo huggingface.co/spaces/prs-eth/rollingdepthhttps://t.ly/sP9ma
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🩷Dance vs. #ComputerVision🩷

👉The Saint-Etienne university proposed a new 3D human body pose estimation pipeline to deal with dance analysis. Project page w/ results and interactive demo released💙

👉Review https://t.ly/JEdM3
👉Paper arxiv.org/pdf/2505.07249
👉Project https://lnkd.in/dD5dsMv5
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🧞‍♀️GENMO: Generalist Human Motion 🧞‍♀️

👉#Nvidia presents GENMO, a unified Generalist Model for Human Motion that bridges motion estimation and generation in a single framework. Conditioning on videos, 2D keypoints, text, music, and 3D keyframes. No code at the moment🥲

👉Review https://t.ly/Q5T_Y
👉Paper https://lnkd.in/ds36BY49
👉Project https://lnkd.in/dAYHhuFU
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Dear friends,
I’m truly sorry for being away from the group for so long. I know: no updates so far while AI is running faster than speed of light.

I’m going through a very difficult time in my life and I need some space to heal. This spare-time project (but important for a lot of people here) needs energy and commitment I don’t have right now. I’m sorry, be patient. I’ll be back.

Love u all,
Alessandro.
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Hi everybody,
I took a few weeks to take a breath from a lot of stuff, I dedicated all my mental energy to keep working and I dedicated all my spare time to take care of myself. Despite I'm still not ok (BTW, my health was/is always good), I feel it's time to come back and support this wonderful community in this journey. I feel the responsibility of that, time to get in the ring.

I'm very sorry for being out so long, but sometime life hits really hard. I got an incredible support from unknown people from all around the world. It's amazing.

Thanks again, you rock!
Alessandro.
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🦖 DINOv3 is out 🦖

👉#Meta unveils DINOv3! A novel foundation model outperforming the previous SOTAs in computer vision. Code & weights released under DINOv3 License💙

👉Review https://t.ly/-S3ZL
👉Paper https://t.ly/ervOT
👉Project https://lnkd.in/dHFf3esd
👉Repo https://lnkd.in/dPxhDxAq
🤗HF https://lnkd.in/dWGudY2i
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🤖 Impact of SuperHuman AI 🤖

👉The NoProfit AI Futures Project unveils a (dystopic) scenario about what super-AI might look like. Forecast from today to the bio-engineered human-like creatures. A fascinating speculation of the future with the "slow-down" and "race" scenarios. Enjoy 💙

👉Review https://t.ly/EgmfJ
👉Project https://ai-2027.com/
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🏓TOTNet: Occlusion-aware Tracking🏓

👉TOTNet: novel Temporal Occlusion Tracking Network that leverages 3D-convs, visibility-weighted loss, & occlusion augmentation to improve performance under occlusions. Code & Data under MIT💙

👉Review https://t.ly/Q0jAf
👉Paper https://lnkd.in/dUYsa-GC
👉Repo https://lnkd.in/d3QGUHYb
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🔀Feed-Forward 4D video🔀

👉4DNeX is the first feed-forward framework for generating 4D scene representations from a single image by fine-tuning diffusion model. HQ dynamic pt-clouds & downstream tasks such as novel-view video synthesis with strong generalizability. Code/Data announced 💙

👉Review https://t.ly/SpkD-
👉Paper arxiv.org/pdf/2508.13154
👉Project https://4dnex.github.io/
👉Repo github.com/3DTopia/4DNeX
👉Data https://lnkd.in/dh4_3Ghf
👉Demo https://lnkd.in/dztyzwgg
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🌈DAViD: Synthetic Depth-Normal-Segmentation🌈

👉#Microsoft's DAViD: 100% synthetic dataset/models for human Depth, Normals & Segmentation. Dataset available, models & runtime under MIT💙

👉Review https://t.ly/-SlO_
👉Paper https://lnkd.in/eCmMXpTg
👉Project https://lnkd.in/eurCSWkm
👉Repo https://lnkd.in/e7PWFgP2
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👠 OmniTry: Virtual Try-On Anything 👠

👉OmniTry: unified framework that extends VTON beyond garment to encompass any wearable objects (jewelries, accessories, etc.) in mask-free setting. Weights, HF demo & benchmark released💙

👉Review https://t.ly/wMBGQ
👉Paper https://lnkd.in/dQe9MchS
👉Project https://omnitry.github.io/
👉Repo https://lnkd.in/d3QwAXY2
🤗Demo https://lnkd.in/duUcZpVA
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📡 ROVR Open Dataset is out 📡

👉A novel large-scale open 3D dataset for autonomous driving, robotics, and 4D perception tasks. To be released for academic (for free) & commercial💙

👉Review https://t.ly/iDcvg
👉Paper https://arxiv.org/pdf/2508.13977
👉Project https://xiandaguo.net/ROVR-Open-Dataset
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🧉 YOPO: SOTA 9-DoF Pose🧉

👉Pit In Co. unveils YOPO, a novel single-stage, query-based framework that treats category-level 9-DoF estimation as a natural extension of 2D detection. A practical solution for mono-RGB, category-level, multi-obj pose estimation. Code & models announced (coming)💙

👉Review https://t.ly/cf_Cl
👉Paper https://arxiv.org/pdf/2508.14965
👉Project mikigom.github.io/YOPO-project-page/
👉Repo TBA
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🔬Intern-S1: SOTA MM-MoE 🔬

👉InternS1: a MM-MoE with 28B activated / 241b total parameters, continually pre-trained on 5T tokens, including 2.5T+ tokens from scientific domains. New SOTA for professional tasks, such as molecular synthesis planning, reaction condition prediction, etc. Models available under Apache 2.0💙

👉Review https://t.ly/3l5UW
👉Paper arxiv.org/pdf/2508.15763
👉Repo github.com/InternLM/Intern-S1
🤗HF huggingface.co/internlm/Intern-S1
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🫔ATLAS: SOTA Human Model🫔

👉#META presents ATLAS, a novel high-fidelity body model learned from 600k high-res. scans captured using 240 synchronized cams. Code announced, to be released💙

👉Review https://t.ly/0hHud
👉Paper arxiv.org/pdf/2508.15767
👉Project jindapark.github.io/projects/atlas/
👉Repo TBA
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🧤Diffusive Hand from Signs🧤

👉LIGM + #NVIDIA unveil a novel generative model of 3D hand motions from Sign Language Data. Motion characteristics such as handshapes, locations, finger, hand & arm movements. Code, Models & Data to be released 💙

👉Review https://t.ly/HonX_
👉Paper https://arxiv.org/pdf/2508.15902
👉Project https://imagine.enpc.fr/~leore.bensabath/HandMDM/
👉Data drive.google.com/drive/u/1/folders/1BLsu2hAqhAJ_gnGb9TNXW7MLiSuSEzEj
👉Repo TBA
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🏎️ VROOM: F1 Reconstruction 🏎️

👉Berkeley unveils VROOM, the first attempt for reconstructing 3D models of #Formula1 circuits using only onboard camera footage from racecars. Extreme challenges due to noise & speed. Repo released💙

👉Review https://t.ly/uuHdT
👉Paper arxiv.org/pdf/2508.17172
👉Repo github.com/yajatyadav/vroom
👉Project varun-bharadwaj.github.io/vroom/
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🥶 OmniHuman-1.5 🥶

👉#ByteDance proposes a novel framework designed to generate character animations that are not only physically plausible but also semantically coherent and expressive. Coherency with speech's rhythm, prosody and semantic content. Impressive results but no code 🥺

👉Review https://t.ly/CnRmX
👉Paper arxiv.org/pdf/2508.19209
👉Project omnihuman-lab.github.io/v1_5/
👉Repo 🥺
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