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AI with Papers - Artificial Intelligence & Deep Learning

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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📈 Telegram kanali AI with Papers - Artificial Intelligence & Deep Learning analitikasi

AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 17 168 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 718-o'rinni va Malayziya mintaqasida 2 234-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 17 168 obunachiga ega bo‘ldi.

20 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -169 ga, so‘nggi 24 soatda esa 0 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 22.86% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining N/A% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 3 926 marta ko‘riladi; birinchi sutkada odatda 0 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 26 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent framework, object, dataset, tba, depth kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
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

Yuqori yangilanish chastotasi (oxirgi ma’lumot 21 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

17 168
Obunachilar
Ma'lumot yo'q24 soatlar
-357 kunlar
-16930 kunlar
Postlar arxiv
🔥21,000+ Hours Dataset🔥 👉SpatialVID is a novel large-scale video dataset with explicit spatial annotations including camera poses, depth maps, structured captions and serialized motion instructions. The dataset consists of 7,089 hours of real-world dynamic scenes. Repo & Dataset Apache-2.0 💙 👉Review https://t.ly/Y9o5k 👉Paper arxiv.org/pdf/2509.09676 👉Project nju-3dv.github.io/projects/SpatialVID/ 👉Repo github.com/NJU-3DV/spatialVID

🐙Human-Centric Video Generation🐙 👉Tsinghua & #ByteDance unveil HuMo: a unified, human-centric video generation framework designed to produce HQ fine-grained, and controllable human videos from multimodal inputs. It supports strong text prompt following, consistent subject preservation, synchronized audio-driven motion. Repo released under Apache2.0💙 👉Review https://t.ly/3S8Yb 👉Paper https://arxiv.org/pdf/2509.08519 👉Project https://phantom-video.github.io/HuMo/ 👉Repo https://github.com/Phantom-video/HuMo

🌱 FoMo4Wheat Foundational Model 🌱 👉PheniX Lab et al. unveil a novel family of foundational models tailored for wheat image tasks, suitable for classification, detection, counting and segmentation. Demo, Dataset, Model & Code under MIT💙 👉Review https://t.ly/UzM-Z 👉Paper arxiv.org/pdf/2509.06907 👉Project fomo4wheat.phenix-lab.com/ 👉Repo github.com/PheniX-Lab/FoMo4Wheat? 👉Demo fomo4wheat.phenix-lab.com/demos

👻 From Skin to Skeleton 👻 👉This paper try unifying the SMPL body model with BSM, a new Biomechanical Skeleton Model. The SKEL model is animatable like SMPL but with fewer, and biomechanically-realistic, degrees of freedom. Model, code, and data available for research💙 👉Review https://t.ly/JsI8M 👉Paper arxiv.org/pdf/2509.06607 👉Project https://skel.is.tue.mpg.de/

🩸Foundation Red Blood Cells🩸 👉RedDino from University of Cagliari is a self-supervised foundation model designed for red blood cell (RBC) morphology analysis. Trained on 1.25M RBC images, it's the new SOTA in shape classification. Code & Models released under Apache2.0💙 👉Review https://t.ly/uWAch 👉Paper https://arxiv.org/pdf/2508.08180 👉Code https://github.com/Snarci/RedDino 👉Models huggingface.co/collections/Snarcy/reddino-689a13e29241d2e5690202fc

🖌️Real-Time Drag-Based Editing🖌️ 👉The Visual AI Lab unveils Inpaint4Drag, a novel framework that decomposes drag-based editing into pixel-space bidirectional warping/inpainting. Inspired by elastic object deformation. Demo and Code released (unknown license)💙 👉Review https://t.ly/H5nlR 👉Paper https://arxiv.org/pdf/2509.04582 👉Project https://visual-ai.github.io/inpaint4drag/ 👉Repo https://github.com/Visual-AI/Inpaint4Drag 👉Demo https://colab.research.google.com/drive/1fzoyNzcJNZjM1_08FE9V2V20EQxGf4PH

Friends, I’ve just open my IG account: https://www.instagram.com/aleferra.ig | Feel free to add me What about posting stuff a
Friends, I’ve just open my IG account: https://www.instagram.com/aleferra.ig | Feel free to add me What about posting stuff about AI on IG? Thoughts?

✂️ #AI Open-Source Annotation ✂️ 👉VisioFirm by TOELT is a fully open-source, AI-powered image annotation tool designed to accelerate labeling for #computervision tasks like object detection, oriented BBs, and segmentation. Source code released under Apache 2.0💙 👉Review https://t.ly/MoMvv 👉Paper https://lnkd.in/dxTncSgv 👉Repo https://lnkd.in/dCWMXp3x

✂️ #AI Open-Source Annotation ✂️ 👉VisioFirm by TOELT is a fully open-source, AI-powered image annotation tool designed to accelerate labeling for hashtag#computervision tasks like object detection, oriented BBs, and segmentation. Source code released under Apache 2.0💙 👉Review https://t.ly/MoMvv 👉Paper https://lnkd.in/dxTncSgv 👉Repo https://lnkd.in/dCWMXp3x

🔥WebEyeTrack: real-time/web eye🔥 👉WebEyeTrack is a novel framework that integrates lightweight SOTA gaze estimation models directly in the browser. Bringing deep‑learning gaze estimation to the web browser and explicitly accounts for head pose. Source Code released under MIT license💙 👉Review https://t.ly/Xon9h 👉Paper https://arxiv.org/pdf/2508.19544 👉Project redforestai.github.io/WebEyeTrack/ 👉Repo github.com/RedForestAi/WebEyeTrack

🍐 Promptable Human Mesh 🍐 👉PromptHMR is a promptable human pose/shape (HPS) estimation method that processes images with spatial or semantic prompts. It takes “side information” readily available from vision-language models or user input to improve the accuracy and robustness of 3D HPS. Code released under Non-Commercial Scientific Research Use Only 💙 👉Review https://t.ly/zJ7S- 👉Paper arxiv.org/pdf/2504.06397 👉Project yufu-wang.github.io/phmr-page/ 👉Repo github.com/yufu-wang/PromptHMR

🐉 #DoubleDragon with #AI 🐉 👉How Double Dragon would look like in real life? Each character has been transformed with #AI to capture their style, fighting spirit, and charisma, as if they had stepped right out of the game’s streets into the real world. AUDIO ON. Damn romantic💙 #artificialintelligence #machinelearning #ml #AI #deeplearning #computervision #AIwithPapers #metaverse #LLM 👉Post https://t.ly/0IpER 👉Channel http://www.youtube.com/@iaiaoh84

🧬 OpenVision 2 is out! 🧬 👉UCSC releases OpenVision2: a novel family of generative pretrained visual encoders that removes
🧬 OpenVision 2 is out! 🧬 👉UCSC releases OpenVision2: a novel family of generative pretrained visual encoders that removes the text encoder and contrastive loss, training with caption-only supervision. Fully open, Apache 2.0💙 👉Review https://t.ly/Oma3w 👉Paper https://arxiv.org/pdf/2509.01644 👉Project https://ucsc-vlaa.github.io/OpenVision2/ 👉Repo https://github.com/UCSC-VLAA/OpenVision

Could you please help me with this poll? https://t.ly/3c3Aa Thanks, A.

🫛TMR: Few-Shot Template-matching🫛 👉POSTECH unveils TMR, a novel and simple template-matching detector for few-shot pattern detection, achieving strong (and SOTA) results on diverse datasets. A new dataset (RPINE) released, repo soon💙 👉Review https://t.ly/WWAcL 👉Paper https://lnkd.in/dJbSu5vk 👉Project https://lnkd.in/dwcDnHHQ 👉Repo https://lnkd.in/dp7aw8Cs

🪴 Pixie: Physics from Pixels 🪴 👉UPenn + MIT unveil Pixie: training a neural-net that maps pretrained visual features (i.e., CLIP) to dense material fields of physical properties in a single forward pass, enabling real‑time physics simulations. Repo & Dataset under MIT license💙 👉Review https://t.ly/1W0n5 👉Paper https://lnkd.in/dsHAHDqM 👉Project https://lnkd.in/dwrHRbRc 👉Repo https://lnkd.in/dy7bvjsK

❤️‍🔥PHD: Personalized 3D Humans❤️‍🔥 👉ETH & #Meta unveil PHD, a novel approach for personalized 3D human mesh recovery (HMR) and body fitting that leverages user-specific shape information to improve pose estimation accuracy. Code & models to be released💙 👉Review https://t.ly/IeRhH 👉Paper https://arxiv.org/pdf/2508.21257 👉Project https://phd-pose.github.io/ 👉Repo TBA

🌈 Multi-View 3D Tracking 🌈 👉MVTracker is the first data-driven multi-view 3D point tracker for tracking arbitrary 3D points across multiple cameras. Repo available💙 👉Review https://t.ly/rISMR 👉Paper arxiv.org/pdf/2508.21060 👉Project https://lnkd.in/drHtAmRC 👉Repo https://lnkd.in/d4k8mg3B

🉐Dress&Dance: Dress-up & Dance🉐 👉Dress&Dance: diffusion framework that generates HQ 5-second-long 24 FPS VTON videos at 1152×720 of a user wearing desired garments while moving in accordance with a given reference video. Impressive results but no repo announced🥺 👉Review https://t.ly/7NeTL 👉Paper https://arxiv.org/pdf/2508.21070 👉Project https://immortalco.github.io/DressAndDance/ 👉Repo 🥺

🌹ROSE: Remove Objects & Effects🌹 👉A novel framework that systematically fix the object’s effects on environment: shadows, reflections, light, translucency and mirror. Model, Demo & Dataset available via Hugging Face💙 👉Review https://t.ly/_KFM0 👉Paper https://lnkd.in/dNcTXQAE 👉Project https://lnkd.in/dFGmYT5h 👉Model https://lnkd.in/dhTT-VkN 👉Demo https://lnkd.in/dimgXZT6 👉Data https://lnkd.in/da7Jv667

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