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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

إظهار المزيد

📈 نظرة تحليلية على قناة تيليجرام AI with Papers - Artificial Intelligence & Deep Learning

تُعد قناة AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 17 151 مشتركاً، محتلاً المرتبة 7 726 في فئة التكنولوجيات والتطبيقات والمرتبة 2 240 في منطقة ماليزيا.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 17 151 مشتركاً.

بحسب آخر البيانات بتاريخ 21 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -166، وفي آخر 24 ساعة بمقدار -6، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 23.63‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 6.86‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 4 057 مشاهدة. وخلال اليوم الأول يجمع عادةً 1 177 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 26.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل framework, object, dataset, tba, depth.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
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

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 22 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.

17 151
المشتركون
-624 ساعات
-277 أيام
-16630 أيام
أرشيف المشاركات
↘️ SEELE: "moving" the subjects ➡️ 👉Subject repositioning: manipulating an input image to reposition one of its subjects to a desired location while preserving the image’s fidelity. SEELE is a single diffusion model to address this novel generative sub-tasks 👉Review https://t.ly/4FS4H 👉Paper https://arxiv.org/pdf/2401.16861.pdf 👉Project https://yikai-wang.github.io/seele/

🥓 RANSAC -> PARSAC (neural) 🥓 👉Neural PARSAC: estimating multiple vanishing points (V), fundamental matrices (F) or homogr
🥓 RANSAC -> PARSAC (neural) 🥓 👉Neural PARSAC: estimating multiple vanishing points (V), fundamental matrices (F) or homographies (H) at the speed of light! Source Code released 💙 👉Review https://t.ly/r9ngg 👉Paper https://lnkd.in/dadQ4Qec 👉Code https://lnkd.in/dYp6gADd

🍋 Diffutoon: new SOTA video 🍋 👉Diffutoon is a cartoon shading approach, aiming to transform photorealistic videos in anime styles. It can handle exceptionally high resolutions and rapid motions. Source code released! 👉Review https://t.ly/sim2O 👉Paper https://lnkd.in/dPcSnAUu 👉Code https://lnkd.in/d9B_dGrf 👉Project https://lnkd.in/dpcsJcX2

🧠350+ Free #AI Courses by #Google🧠 👉350+ free courses from #Google to become professional in #AI & #Cloud. The full catalo
🧠350+ Free #AI Courses by #Google🧠 👉350+ free courses from #Google to become professional in #AI & #Cloud. The full catalog (900+) includes a variety of activity: videos, documents, labs, coding, and quizzes. 15+ supported languages. No excuse. ✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 ✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐋𝐋𝐌𝐬 ✅𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐓𝐅 ✅𝐁𝐚𝐬𝐞𝐥𝐢𝐧𝐞 𝐃𝐚𝐭𝐚, 𝐌𝐋, 𝐀𝐈 ✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐀𝐈 👉Review: https://t.ly/517Dr 👉Full list: https://www.cloudskillsboost.google/catalog?page=1

🐙 Rock-Track announced! 🐙 👉Key Lab of Robotics and System announced Rock-Track, the evolution of Poly-MOT, the previous SOTA in 3D MOT Tracking-By-Detection framework. 👉Review https://t.ly/hC0ak 👉Repo, coming: https://lnkd.in/dtDkPwCC 👉Paper coming

🌋EasyVolcap: Accelerating Neural Volumetric🌋 👉Novel #PyTorch library for accelerating neural volumetric video research: volumetric video capturing, reconstruction & rendering 👉Review https://t.ly/8BISl 👉Paper arxiv.org/pdf/2312.06575.pdf 👉Code github.com/zju3dv/EasyVolcap

🦩 WildRGB-D: Objects in the Wild 🦩 👉#NVIDIA unveils a novel RGB-D object dataset captured in the wild: ~8500 recorded objects, ~20,000 RGBD videos, 46 categories with corresponding masks and 3D point clouds. 👉Review https://t.ly/WCqVz 👉Data github.com/wildrgbd/wildrgbd 👉Paper arxiv.org/pdf/2401.12592.pdf 👉Project wildrgbd.github.io/

👢"Virtual Try-All" by #Amazon 👢 👉#Amazon announces ”Diffuse to Choose”: diffusion-based image-conditioned inpainting for VTON. Virtually place any e-commerce item in any setting. 👉Review https://t.ly/at07Y 👉Paper https://lnkd.in/dxR7nGtd 👉Project diffuse2choose.github.io/

🫧 SAM + Open-Models 🫧 👉Grounded SAM (w/ DINO) as an open-set detector to combine with SAM. This integration enables the detection and segmentation of any regions based on arbitrary text inputs and opens a door to connecting various vision models. It can seamlessly integrate with other Open-World models to accomplish more intricate visual tasks. 👉Review https://t.ly/FwasQ 👉Paper https://arxiv.org/pdf/2401.14159.pdf 👉Code https://github.com/IDEA-Research/Grounded-Segment-Anything

🧪 SUPIR: SOTA restoration 🧪 👉SUPIR is the new SOTA in image restoration; suitable for restoration of blurry objects, defining the material texture of objects, and adjusting restoration based on high-level semantics 👉Review https://t.ly/wgObH 👉Project https://lnkd.in/dPcnBKWm 👉Paper https://lnkd.in/dZPYcUuq 👉Demo coming 🩷 but no code announced :(

🔥Lumiere: SOTA video-gen🔥 👉#Google unveils Lumiere: Space-Time Diffusion Model for Realistic Video Generation. It's the new SOTA, tasks: Text-to-Video, Video Stylization, Cinemagraphs & Video Inpainting. 👉Review https://t.ly/nalJR 👉Paper https://lnkd.in/d-PvrGjT 👉Project https://t.ly/gK8hz

🎭 UltrAvatar: ULTRA-Realistic Avatar 🎭 👉Novel 3D avatar with enhanced fidelity of geometry, and superior quality of physically based rendering (PBR) textures without unwanted lighting. 👉Review https://t.ly/B3BEu 👉Project https://lnkd.in/dkUQHFEV 👉Paper https://lnkd.in/dtEQxrBu 👉Code coming 🩷

🔥 Depth Anything: the new SOTA 🔥 👉Depth Anything: the new SOTA in monocular depth estimation (MDE), trained with 1.5M labeled images and 62M+ unlabeled images jointly. It's the new SOTA! Authors: University of Hong Kong, #TikTok, Zhejiang Lab & Zhejiang University. Paper, project, code, models & HF-demo released! 👉Review https://t.ly/tCBwO 👉Paper https://lnkd.in/djx-9k2J 👉Project https://lnkd.in/dYetqZFa 👉Repo https://lnkd.in/d87CrUGv 👉Demo🤗 https://lnkd.in/dJhvKBep

😻 GARField: Group Anything 😻 👉 GARField is a novel approach for decomposing #3D scenes into a hierarchy of semantically meaningful groups from posed image inputs. 👉Review https://t.ly/6Hkeq 👉Paper https://lnkd.in/d28mfRcZ 👉Project https://lnkd.in/dzYdRNKy 👉Repo (coming) https://lnkd.in/d2VeRJCS

👽 One Model <-> All Segmentations 👽 👉 10+ different segmentation tasks in one framework, including image-level, vide
👽 One Model <-> All Segmentations 👽 👉 10+ different segmentation tasks in one framework, including image-level, video-level, interactive segmentation, & open-vocabulary segmentation. 👉Review https://t.ly/fywVz 👉Paper https://lnkd.in/dw3S4B74 👉Project https://lnkd.in/dzHT9v45 👉Repo https://lnkd.in/d6fDCnSp

🦠 XINC: Pixels to Neurons 🦠 👉eXplaining the Implicit Neural Canvas (XINC) from the University of Maryland, is a unified framework for explaining properties of INRs by examining the strength of each neuron’s contribution to each output pixel 👉Review https://t.ly/wwAmz 👉Paper arxiv.org/pdf/2401.10217.pdf 👉Project namithap10.github.io/xinc 👉Repo github.com/namithap10/xinc

🫒 AlphaGeometry: Olympiad-level AI 🫒 👉 Theorem prover for Euclidean plane geometry that sidesteps the need for human demon
🫒 AlphaGeometry: Olympiad-level AI 🫒 👉 Theorem prover for Euclidean plane geometry that sidesteps the need for human demonstrations by synthesizing millions of theorems and proofs across different levels of complexity 🤯 👉Review https://t.ly/2-Z7C 👉Paper https://lnkd.in/g3QkqwCE 👉Blog https://lnkd.in/ge-mpM7q 👉Repo https://lnkd.in/gHjwks_9

🔥🔥 Code is out 🔥🔥 Check the comments for the links ;)

💃Timeline Text-Driven Humans💃 👉Novel challenge: timeline control for text-driven motion synthesis of 3D Humans. 👉Review https://t.ly/HLm-N 👉Paper https://lnkd.in/esaR_M_9 👉Project https://lnkd.in/epCZDvFW 👉Repo coming

💥 Announcing #Py4Ai Conference💥 👉 Super proud to unveil #Py4AI, the newest conference dedicated to exploring the depths of Python & AI. Py4AI is a 1-day free event for Python and Artificial Intelligence developers. 𝐄𝐯𝐞𝐧𝐭 𝐃𝐞𝐭𝐚𝐢𝐥𝐬: ✅16th March 2024 (Saturday) - all day long! ✅Location: Pavia, at SEA Vision HQ ✅Seats: first 100 available now! ✅Live streaming: YES 🌍 ✅Cost: it's 100% FREE! We will investigate the latest trends, advancements, and challenges in Artificial Intelligence: NLP, MLOps, Computer Vision, Machine Learning & Generative AI! A scientific conference with international speakers. Only Science, Coding & professionals in AI. And beers, of course. 𝐓𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐛𝐚𝐭𝐜𝐡 𝐨𝐟 𝐬𝐩𝐞𝐚𝐤𝐞𝐫𝐬: 🚀Merve Noyan | ML Advocate Eng. Hugging Face 🤗 🚀Gabriele Lombardi | CTO ARGO Vision 🚀Amanda Cercas Curry | PostDoc. Università Bocconi 🚀Piero Savastano | Founder Cheshire Cat AI 🚀Francesco Zuppichini | Sr. ML engineer Zurich Insurance 🚀Andrea Palladino, PhD | Sr. Data Scientist 👉 More: https://www.linkedin.com/posts/visionarynet_py4ai-py4ai-python-activity-7152928716988243968-pOUn?utm_source=share&utm_medium=member_desktop

AI with Papers - Artificial Intelligence & Deep Learning - إحصائيات وتحليلات قناة تيليجرام @ai_deeplearning