اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
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
نمایش بیشتر📈 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 17 202 مشترک است و جایگاه 7 717 را در دسته فناوری و برنامهها و رتبه 2 233 را در منطقه ماليزيا دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 17 202 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 13 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -130 و در ۲۴ ساعت گذشته برابر -4 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 19.56% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً N/A% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 3 365 بازدید دریافت میکند. در اولین روز معمولاً 0 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 19 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 14 ژوئن, 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.
17 202
مشترکین
-424 ساعت
-327 روز
-13030 روز
آرشیو پست ها
🍧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
