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 17 146 مشترک است و جایگاه 7 718 را در دسته فناوری و برنامهها و رتبه 2 244 را در منطقه ماليزيا دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 17 146 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 22 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -178 و در ۲۴ ساعت گذشته برابر -15 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 24.30% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 6.86% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 4 167 بازدید دریافت میکند. در اولین روز معمولاً 1 177 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 26 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 23 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.
17 146
مشترکین
-1524 ساعت
-437 روز
-17830 روز
آرشیو پست ها
💊💊 AGNOSTIC Object Counting 💊💊
👉PseCo: combining SAM to segment all possible objects as mask proposals & CLIP to classify proposals to obtain accurate object counts. The new SOTA in both few-shot/zero-shot object counting/detection.
👉Discussion https://lnkd.in/dMgakzWm
👉Paper https://lnkd.in/dbzMXKWG
👉Repo https://lnkd.in/db9Q9Pse
🥛 Transparent Object Tracking 🥛
👉Trans2k: transparent object tracking dataset of 2,000+ sequences with 100,000+ images, annotated by bounding boxes & segmentation mask.
👉Review https://t.ly/mEI6O
👉Paper https://lnkd.in/dsudY3DB
👉Project https://lnkd.in/d48SSJJ3
👉TOB https://lnkd.in/dykBUNfC
🃏ReplaceAnything: demo is out!🃏
👉ReplaceAnything: ultra-high quality content replacement. The ultimate #AI solution for human, clothing & background replacement to change the e-commerce experience for vendors.
👉Review https://t.ly/FMyvf
👉Project https://lnkd.in/dcyZvP2b
👉ModelScope https://lnkd.in/dU4x4nE6
👉Hugging Face https://lnkd.in/dn3uXWgd
👉Empty report https://lnkd.in/dcuGXd6c
👉Paper coming?
🔥 #6D Foundation Pose 🔥
👉#Nvidia unveils FoundationPose, a novel (and unified) foundation model for 6D object pose estimation and tracking.
👉Review https://t.ly/HGd4h
👉Project https://lnkd.in/dPcnBKWm
👉Paper https://lnkd.in/dixn_iHZ
👉Code coming 🩷
🐤 MagicVideo-V2 Video Generation 🐤
👉#Bytedance announces a novel multi-stage pipeline capable of generating high-aesthetic videos from textual description
👉Review https://t.ly/zIq4v
👉Project https://lnkd.in/dKUrJPJd
👉Paper https://lnkd.in/dixnN-kU
🕍 En3D: Generative 3D Humans 🕍
👉#Alibaba unveils En3D: generative scheme for sculpting HQ 3D human avatars. Zero-shot 3D generative scheme capable of producing visually realistic, geometrically accurate and content-wise diverse 3D humans without relying on pre-existing 3D or 2D asset.
👉Review https://t.ly/nGmDK
👉Project menyifang.github.io/projects/En3D/index.html
👉Paper https://arxiv.org/pdf/2401.01173.pdf
👉Repo (coming) https://github.com/menyifang/En3D
👻 W2A: Avatar Behind Occlusions 👻
👉Neural rendering for occluded in-the-wild mono-videos. Decoupling scenes in occlusion, human, and background.
👉Review https://t.ly/8q__B
👉Paper https://arxiv.org/pdf/2401.00431.pdf
👉Project https://cs.stanford.edu/~xtiange/projects/wild2avatar
🈚 Seeing Through Occlusions 🈚
👉Princeton University unveils a novel NSF approach able to fuse a burst image capture into one high-resolution reconstruction and decompose it into transmission and obstruction layers. Tasks: seeing through occlusions, reflection suppression, shadow removal
👉Review https://t.ly/5jcIG
👉Project https://light.princeton.edu/publication/nsf/
👉Paper https://arxiv.org/pdf/2312.14235.pdf
👉Repo https://github.com/princeton-computational-imaging/NSF
🪲UniRef++: Segment Every Reference🪲
👉 UniRef++ is a unified model for RIS, FSS, RVOS & VOS. Code available!
👉Review https://t.ly/OxtOx
👉Paper https://lnkd.in/eTrmDTK3
👉Repo https://lnkd.in/etfTm4Wq
🪮HAAR: Text-Driven Generative Hairstyles🪮
👉 HAAR: new strand-based generative model for #3D human hairstyles driven by textual input.
👉Review https://t.ly/L38iD
👉Project https://haar.is.tue.mpg.de/
👉Paper https://arxiv.org/pdf/2312.11666.pdf
👉Repo coming
🎄UniSDF: Unifying Neural Representations🎄
👉UniSDF: novel general purpose 3D reconstruction for large complex scenes with reflections. SOTA on DTU, Shiny Blender, Mip-NeRF 360 and Ref-NeRF dataset.
👉Review https://t.ly/2QEul
👉Paper https://arxiv.org/pdf/2312.13285.pdf
👉Repo: No code :(
🚿 Event-Camera (1000 fps) Hands 🚿
👉Ev2Hands, the first method for the 3D reconstruction of two interacting hands from a single event camera. Code available.
👉Review https://t.ly/YpQpX
👉Paper https://arxiv.org/pdf/2312.14157.pdf
👉Project https://4dqv.mpi-inf.mpg.de/Ev2Hands
👉Repo https://github.com/Chris10M/Ev2Hands
🖲️ Amodal Tracking Any Object 🖲️
👉Amodal tracking": inferring complete object boundaries, even when certain portions are occluded. New benchmark & approach, 2x better than SOTA in people tracking 🔥
👉Review https://t.ly/Rc6Ku
👉Paper https://lnkd.in/d39rFYT4
👉Project https://lnkd.in/d7bkEcni
👉(empty) Repo https://lnkd.in/dTsNKdfz
🧊 ControlNet for Depth Conditioning 🧊
👉KAUST (+ #Adobe) unveils LooseControl to control the generative image modeling process. Layout by boundaries and #3D box control via object locations (approximate bounding boxes). A step forward in generative design of the products.
#artificialintelligence #machinelearning #ml #AI #deeplearning #computervision #AIwithPapers #metaverse
👉Review https://t.ly/9y72m
👉Paper https://arxiv.org/pdf/2312.03079.pdf
👉Project https://shariqfarooq123.github.io/loose-control/
👉Demo🤗 https://huggingface.co/spaces/shariqfarooq/LooseControl
👉Repo https://github.com/shariqfarooq123/LooseControl
🔥 #AIwithPapers: we are 8k+ 🔥
👉 After flirting with #ChatGpt for months, you back in love with this channel and #ComputerVision. I felt bad but I forgive you 🧡
😈 What about boosting us channel? Click: https://t.me/AI_DeepLearning?boost
😈Invite -> https://t.me/AI_DeepLearning
💃Outfit Anyone: Ultra-HQ VTO💃
👉Alibaba unveils Outfit Anyone: a two-stream conditional diffusion able to adeptly handle garment deformation for more lifelike results in VOT. Extra: Outfit Anyone + Animate Anyone for outfit + motion generation of any character. NO CODE / NO PAPER / DEMO AVAILABLE :)
👉Review https://t.ly/o6UR9
👉Demo https://lnkd.in/dpQYdXhc
👉Repo (empty) https://lnkd.in/dBsNST6r
🪼 PatchFusion: SOTA Mono-Depth 🪼
👉PatchFusion: novel end-to-end tile-based framework for hi-res monocular metric depth estimation. It's the new SOTA in metric depth estimation from mono. Code & Demo on Hugging Face able 🔥
👉Review https://t.ly/hv3yT
👉Paper https://lnkd.in/d9dXP7iP
👉Project https://lnkd.in/dQcvVJSx
👉Repo https://lnkd.in/dW2GdVR5
👉Demo https://lnkd.in/dFW-gAiY
📲 EdgeSAM: On-Device 40x SAM 📲
👉A novel hyper-optimized version of SAM for mobile devices such as #Iphone. Pure CNNs backbone (better suitable for ANE), up to 40x faster!
👉Review https://t.ly/m_vLH
👉Paper https://lnkd.in/gHZVZN2x
👉Project https://lnkd.in/gK8qEK8p
👉Repo https://lnkd.in/gj6YAGNv
👉Hugging Face https://lnkd.in/gUUHJvxz
🪩 DreaMoving: Human Generation 🪩
👉Alibaba strikes again with DreaMoving: a diffusion-based controllable video generation framework to produce HQ customized human videos.
👉Review https://t.ly/BD_Yf
👉Paper https://lnkd.in/gepP6Rjw
👉Project https://lnkd.in/gwm72cfS
👉Repo (empty) https://lnkd.in/gsc2Qt-F
🫶 #3D Hands with Transformers 🫶
👉 HaMeR is a robust and accurate Hand Mesh Recovery from images and video frames, based on Transformer architecture. It's the new SOTA.
👉Review https://t.ly/YtAW8
👉Paper https://arxiv.org/pdf/2312.05251.pdf
👉Project https://geopavlakos.github.io/hamer
👉Demo huggingface.co/spaces/geopavlakos/HaMeR
👉Colab colab.research.google.com/drive/1rQbQzegFWGVOm1n1d-S6koOWDo7F2ucu
