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 17 053 مشتركاً، محتلاً المرتبة 7 587 في فئة التكنولوجيات والتطبيقات والمرتبة 2 166 في منطقة ماليزيا.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 17 053 مشتركاً.
بحسب آخر البيانات بتاريخ 21 يوليو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -112، وفي آخر 24 ساعة بمقدار -8، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 19.26%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 7.22% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 3 284 مشاهدة. وخلال اليوم الأول يجمع عادةً 1 231 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 15.
- 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 يوليو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
17 053
المشتركون
-824 ساعات
-17 أيام
-11230 أيام
أرشيف المشاركات
🍧Monocular 3D Clothed Human🍧
👉MultiGO++ is a novel framework for monocular 3D clothed human reconstruction via geometry-texture collaboration. New SOTA but no code announced🥲
👉Review https://t.ly/YKY44
👉Paper arxiv.org/pdf/2603.04993
👉Project 3dagentworld.github.io/multigo++
Could be useful for you seeing a few (verified) job posting about AI in this channel?
🍙Any Resolution, Any Geometry🍙
👉Ultra Resolution Geometry Transformer (URGT) for arbitrary resolutions (e.g. 4K, 6K, 8K) depth–normal estimation. New SOTA. Repo under MIT💙
👉Review https://t.ly/HXg1n
👉Paper arxiv.org/pdf/2603.03026
👉Project dreamaker-mrc.github.io/Any-Resolution-Any-Geometry/
👉Repo github.com/Dreamaker-MrC/Any-Resolution-Any-Geometry
🐪DuoMo: Dual Motion Diffusion🐪
👉DuoMo by #Meta is a novel generative method that recovers human motion in world-space coordinates from unconstrained videos with noisy or incomplete observations. Code announced💙
👉Review https://t.ly/dnA3K
👉Paper arxiv.org/pdf/2603.03265
👉Project yufu-wang.github.io/duomo/
👉Repo TBA
🪿All Point Clouds-One Encoder🪿
👉Utonia is a step toward one-from-all and one-for-all point cloud encoder. It pretrains a single encoder on diverse point cloud data and reuses it as a reliable backbone for downstream tasks. Code under Apache 2.0💙
👉Review https://t.ly/yqSyZ
👉Paper https://arxiv.org/pdf/2603.03283
👉Project https://pointcept.github.io/Utonia/
👉Repo https://github.com/Pointcept/Utonia
🍓Fully Offline Mobile-VTON🍓
👉A novel, hq, privacy-preserving framework that enables fully offline virtual try-on on commodity mobile devices using only a single user image and a garment image. Repo announced, to be released💙
👉Review https://t.ly/dsrIn
👉Paper arxiv.org/pdf/2603.00947
👉Project zhenchenwan.github.io/Mobile-VTON/
👉Repo https://github.com/tmllab/2026_CVPR_Mobile-VTON
🦜Geometry-Aware 4D Head🦜
👉 GeoDiff4D is a novel framework that reconstructs animatable 4D head avatars from a single portrait image through geometry-aware diffusion. Code announced💙
👉Review https://t.ly/J9L-t
👉Paper https://lnkd.in/ddpv-78g
👉Project https://lnkd.in/d-vhukyj
👉Repo https://lnkd.in/dzd6mnFv
🧱Solaris: generative #Minecraft🧱
👉NYU unveils Solaris, multiplayer video world model in Minecraft, which generates consistent first-person observations for two players simultaneously. Impressive work. Repo & Dataset💙
👉Review https://t.ly/VrcrT
👉Paper https://arxiv.org/pdf/2602.22208
👉Project https://solaris-wm.github.io/
👉Repo https://github.com/solaris-wm/
🫸 World-Grounded Hand-Object🫸
👉Given SLAMed egocentric videos, unlike existing methods that predict either hands or object poses separately, WHOLE jointly reconstructs coherent hand and object motion in the world space by guiding a generative motion prior. Code announced💙
👉Review https://t.ly/c5w8h
👉Paper https://arxiv.org/pdf/2602.22209
👉Project https://judyye.github.io/whole-www/
👉Repo TBA
🔥New SOTA Planar Tracking🔥
👉WOFTSAM by the Visual Recognition Group (CTU) is a novel planar tracker that combine robust long-term segmentation by SAM2 with 8 degrees-of-freedom homography pose estimation. Repo under BY-NC-SA 4.0💙
👉Review https://t.ly/VUOe5
👉Paper https://lnkd.in/dZfc_DhQ
👉Repo https://lnkd.in/dAcneJGn
🚤Video Neural Compression🚤
👉TeCoNeRV by UMD is a framework for adapting INR hypernetworks to compress videos efficiently at higher resolutions. Impressive results: +5.35dB PSNR @720p on UVG, -36% bitrates & 1.5-3× faster encoding. Code announced💙
👉Review https://t.ly/0AtCK
👉Paper arxiv.org/pdf/2602.16711
👉Project namithap10.github.io/teconerv/
👉Repo github.com/namithap10/TeCoNeRV/
🐙Dex4D: Task-Agnostic Track🐙
👉Dex4D by CMU is a novel approach for unseen objects and poses, scene layouts, backgrounds, & task trajectories. Code under Apache 2.0💙
👉Review https://t.ly/ZGx9T
👉Paper arxiv.org/pdf/2602.15828
👉Project dex4d.github.io/
👉Sim github.com/Dex4D/Dex4D-Simulation
👉Vision github.com/Dex4D/Dex4D-Vision
👉HW https://github.com/Dex4D/Dex4D-Hardware
📲 Efficient VLMs 📲
👉CoPE-VideoLM is a codec-aware tokenization framework for VLM that replaces dense RGB encoding with lightweight structured representations derived from codec primitives. Token -93% / time-to-first-token -86%! Code announced💙
👉Review https://t.ly/3_GqN
👉Paper https://arxiv.org/pdf/2602.13191
👉Project https://sayands.github.io/cope/
👉Repo TBA
🥝Conversational Segmentation🥝
👉CIS grounds abstract, intent-oriented concepts into pixel-accurate masks, reasoning about affordances, physics, and functional properties. Code/Demo released💙
👉Review https://t.ly/SsG57
👉Paper arxiv.org/pdf/2602.13195
👉Project glab-caltech.github.io/converseg/
👉Repo github.com/AadSah/ConverSeg
👉Demo glab-caltech.github.io/converseg/#interactive-demo
🪿Teaching AI to illusions🪿
👉Stroke of Surprise by NYCU is a novel generative framework that optimizes vector strokes to satisfy distinct semantic interpretations at different drawing stages. As strokes are progressively added, the sketch reveals a completely different subject. Code released💙
👉Review https://t.ly/98Oim
👉Paper https://lnkd.in/dTA7iuce
👉Project https://lnkd.in/dhTMGw23
👉Repo https://lnkd.in/deQyDGFu
🫧SurfPhase: 3D Interfacial Dynamics🫧
👉SurfPhase is a novel model for reconstructing 3D interfacial dynamics from sparse camera views. Repo/Dataset announced💙
👉Review https://t.ly/g2P5F
👉Paper https://arxiv.org/pdf/2602.11154
👉Project https://yuegao.me/SurfPhase/
👉Repo github.com/yuegao/SurfPhase
🤖Generalized Human Tracking🤖
👉Beijing Institute of Technology & Humanoid Robotics Shangai present a novel learning framework for general humanoid whole-body control. Impressive results in imitation.
👉Review https://t.ly/ucmuB
👉Paper arxiv.org/pdf/2601.23080
👉Project zeonsunlightyu.github.io/RGMT.github.io
🛠️ IndustryShapes 6D Pose 🛠️
👉IndustryShapes by NTUA is a new RGB-D dataset of industrial tools and components, designed for both instance-level and novel object 6D pose estimation. Dataset available💙
👉Review https://t.ly/KKcuH
👉Paper https://arxiv.org/pdf/2602.05555
👉Project https://pose-lab.github.io/IndustryShapes/
👉Dataset https://huggingface.co/datasets/POSE-Lab/IndustryShapes
🛠️ IndustryShapes 6D Pose 🛠️
👉IndustryShapes by NTUA is a new RGB-D dataset of industrial tools and components, designed for both instance-level and novel object 6D pose estimation. Dataset available💙
👉Discussion https://lnkd.in/dMgakzWm
👉Paper https://arxiv.org/pdf/2602.05555
👉Project https://pose-lab.github.io/IndustryShapes/
👉Dataset https://huggingface.co/datasets/POSE-Lab/IndustryShapes
🍌 AGENT BANANA (SOTA) 🍌
👉Agent Banana is the novel SOTA agentic system for HD, native-resolution image editing through reasoning-based NL interaction, where each edit is context-aware, logically dependent, and locally precise. Code announced💙
👉Review https://t.ly/EXaCH
👉Paper https://arxiv.org/pdf/2602.09084
👉Project https://agent-banana.github.io/
👉Repo https://github.com/taco-group/agent-banana
