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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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📈 تحلیل کانال تلگرام AI with Papers - Artificial Intelligence & Deep Learning

کانال AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 17 261 مشترک است و جایگاه 7 509 را در دسته فناوری و برنامه‌ها و رتبه 2 130 را در منطقه ماليزيا دارد.

📊 شاخص‌های مخاطب و پویایی

از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 17 261 مشترک جذب کرده است.

بر اساس آخرین داده‌ها در تاریخ 25 اکتبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 261 و در ۲۴ ساعت گذشته برابر 2 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.

  • وضعیت تأیید: تأیید نشده
  • نرخ تعامل (ER): میانگین تعامل مخاطب 16.91% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 7.04% واکنش نسبت به کل مشترکان کسب می‌کند.
  • دسترسی پست‌ها: هر پست به طور میانگین 2 918 بازدید دریافت می‌کند. در اولین روز معمولاً 1 216 بازدید جمع‌آوری می‌شود.
  • واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 16 است.
  • علایق موضوعی: محتوا بر موضوعات کلیدی مانند framework, object, dataset, tba, depth تمرکز دارد.

📝 توضیح و سیاست محتوایی

نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
“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”

به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 26 اکتبر, 2026)، کانال همواره به‌روز و دارای دسترسی بالاست. تحلیل‌ها نشان می‌دهد مخاطبان به‌طور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامه‌ها تبدیل کرده‌اند.

17 261
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+224 ساعت
+17 روز
+26130 روز
آرشیو پست ها
🌵 G-Splatting Controllable Portraits 🌵 👉From monocular/casual video captures, Rig3DGS rigs 3D Gaussian Splatting to enable the creation of re-animatable portrait videos with control over facial expressions, head-pose and viewing direction. Authors: Stony Brook University & #Adobe 👉Review https://t.ly/fq71w 👉Paper https://arxiv.org/pdf/2402.03723.pdf 👉Project shahrukhathar.github.io/2024/02/05/Rig3DGS.html

🪵 HASSOD Object Detection 🪵 👉 HASSOD: fully self-supervised detection and instance segmentation. The new SOTA able to understand the part-to-whole object composition like humans do. 👉Review https://t.ly/66qHF 👉Paper arxiv.org/pdf/2402.03311.pdf 👉Project hassod-neurips23.github.io/ 👉Repo github.com/Shengcao-Cao/HASSOD

💥 #Py4AI: 2x speakers, 2x tickets! 💥 ✅Doubling the speakers (6 -> 12!) ✅Adding a new track (2 tracks in parallel) ✅Releasin
💥 #Py4AI: 2x speakers, 2x tickets! 💥 ✅Doubling the speakers (6 -> 12!) ✅Adding a new track (2 tracks in parallel) ✅Releasing a new batch of 100 tickets! 👉 More: https://t.ly/WmVrM

🏇Bootstrapping TAP 🏇 👉#Deepmind shows how large-scale, unlabeled, uncurated real-world data can improve TAP with minimal architectural changes, via a self-supervised student-teacher setup. Source Code released 💙 👉Review https://t.ly/-S_ZL 👉Paper https://arxiv.org/pdf/2402.00847.pdf 👉Code https://lnkd.in/gyi7Dhkn

🍬 ABS: SOTA collision-free 🍬 👉ABS (Agile But Safe): learning-based control framework for agile and collision-free locomotion for quadrupedal robot. Source Code announced (coming) 💙 👉Review https://t.ly/AYu-Z 👉Paper arxiv.org/pdf/2401.17583.pdf 👉Project agile-but-safe.github.io/ 👉Repo github.com/LeCAR-Lab/ABS

🚦(adding) Anything in Any Video🚦🚦 👉 XPeng Motors announced Anything in Any Scene: novel #AI for realistic video simulation that seamlessly inserts any object into an existing dynamic video. Strong emphasis on realism, the objects in the BBs don't exist. Source Code released 💙 👉Review https://t.ly/UYhl0 👉Code https://lnkd.in/gyi7Dhkn 👉Paper https://lnkd.in/gXyAJ6GZ 👉Project https://lnkd.in/gVA5vduD

🚦(adding) Anything in Any Video🚦🚦 👉 XPeng Motors announced Anything in Any Scene: novel #AI for realistic video simulation that seamlessly inserts any object into an existing dynamic video. Strong emphasis on realism, the objects in the BBs don't exist. Source Code released 💙 👉Review https://t.ly/UYhl0 👉Code https://lnkd.in/gyi7Dhkn 👉Paper https://lnkd.in/gXyAJ6GZ 👉Project https://lnkd.in/gVA5vduD

🎉 ADΔER: Event-Camera Suite 🎉 👉ADΔER: a novel/unified framework for event-based video. Encoder / transcoder / decoder for ADΔER (Address, Decimation, Δt Event Representation) video streams. Source code (RUST) released 💙 H/T author: Andrew C. Freeman from University of North Carolina, USA. 👉Review https://t.ly/w5_KC 👉Paper arxiv.org/pdf/2401.17151.pdf 👉Repo github.com/ac-freeman/adder-codec-rs

↘️ 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 🩷