AI with Papers - Artificial Intelligence & Deep Learning
رفتن به کانال در Telegram
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 17 021 مشترک است و جایگاه 7 494 را در دسته فناوری و برنامهها و رتبه 2 177 را در منطقه ماليزيا دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 17 021 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 25 اوت, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -24 و در ۲۴ ساعت گذشته برابر 10 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 22.06% 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 0 بازدید دریافت میکند. در اولین روز معمولاً 0 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 0 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 اوت, 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.
17 021
مشترکین
+1024 ساعت
+107 روز
-2430 روز
در حال بارگیری داده...
کانالهای مشابه
ابر برچسبها
اشارات ورودی و خروجی
---
---
---
---
---
---
جذب مشترکین
اوت '26
اوت '26
+48
در 2 کانالها
ژوئیه '26
+56
در 0 کانالها
Get PRO
ژوئن '26
+52
در 0 کانالها
Get PRO
مه '26
+90
در 0 کانالها
Get PRO
آوریل '26
+207
در 0 کانالها
Get PRO
مارس '26
+718
در 0 کانالها
Get PRO
فوریه '26
+140
در 1 کانالها
Get PRO
ژانویه '26
+2 306
در 0 کانالها
Get PRO
دسامبر '25
+157
در 1 کانالها
Get PRO
نوامبر '25
+201
در 0 کانالها
Get PRO
اکتبر '25
+243
در 1 کانالها
Get PRO
سپتامبر '25
+147
در 3 کانالها
Get PRO
اوت '25
+140
در 0 کانالها
Get PRO
ژوئیه '25
+162
در 0 کانالها
Get PRO
ژوئن '25
+107
در 0 کانالها
Get PRO
مه '25
+152
در 1 کانالها
Get PRO
آوریل '25
+331
در 0 کانالها
Get PRO
مارس '25
+459
در 1 کانالها
Get PRO
فوریه '25
+600
در 0 کانالها
Get PRO
ژانویه '25
+643
در 1 کانالها
Get PRO
دسامبر '24
+542
در 1 کانالها
Get PRO
نوامبر '24
+439
در 2 کانالها
Get PRO
اکتبر '24
+350
در 3 کانالها
Get PRO
سپتامبر '24
+215
در 0 کانالها
Get PRO
اوت '24
+295
در 0 کانالها
Get PRO
ژوئیه '24
+396
در 1 کانالها
Get PRO
ژوئن '24
+439
در 0 کانالها
Get PRO
مه '24
+533
در 0 کانالها
Get PRO
آوریل '24
+483
در 0 کانالها
Get PRO
مارس '24
+501
در 1 کانالها
Get PRO
فوریه '24
+493
در 0 کانالها
Get PRO
ژانویه '24
+522
در 1 کانالها
Get PRO
دسامبر '23
+400
در 0 کانالها
Get PRO
نوامبر '23
+330
در 0 کانالها
Get PRO
اکتبر '23
+298
در 0 کانالها
Get PRO
سپتامبر '23
+482
در 0 کانالها
Get PRO
اوت '23
+136
در 0 کانالها
Get PRO
ژوئیه '23
+173
در 0 کانالها
Get PRO
ژوئن '23
+112
در 0 کانالها
Get PRO
مه '23
+164
در 0 کانالها
Get PRO
آوریل '23
+234
در 0 کانالها
Get PRO
مارس '23
+216
در 0 کانالها
Get PRO
فوریه '23
+400
در 0 کانالها
Get PRO
ژانویه '23
+435
در 0 کانالها
Get PRO
دسامبر '22
+372
در 0 کانالها
Get PRO
نوامبر '22
+5 238
در 0 کانالها
| تاریخ | رشد مشترکین | اشارات | کانالها | |
| 26 اوت | +1 | |||
| 25 اوت | +11 | |||
| 24 اوت | 0 | |||
| 23 اوت | +7 | |||
| 22 اوت | 0 | |||
| 21 اوت | +4 | |||
| 20 اوت | +2 | |||
| 19 اوت | +1 | |||
| 18 اوت | +1 | |||
| 17 اوت | 0 | |||
| 16 اوت | +1 | |||
| 15 اوت | 0 | |||
| 14 اوت | +3 | |||
| 13 اوت | 0 | |||
| 12 اوت | 0 | |||
| 11 اوت | +3 | |||
| 10 اوت | 0 | |||
| 09 اوت | 0 | |||
| 08 اوت | +4 | |||
| 07 اوت | +4 | |||
| 06 اوت | +2 | |||
| 05 اوت | 0 | |||
| 04 اوت | +3 | |||
| 03 اوت | 0 | |||
| 02 اوت | 0 | |||
| 01 اوت | +1 |
پستهای کانال
🍋🟩Remesh-Aware Mesh Deformation🍋🟩
👉RADmesh is a novel generative deformation technique enhanced by remeshing. Given a text prompt, it deforms and remeshes a mesh region to form new geometric features. Repo MIT💙
👉Review https://lnkd.in/p/eK6FZv9c
👉Paper https://arxiv.org/pdf/2608.17182
👉Project https://threedle.github.io/radmesh/
👉Repo https://github.com/threedle/radmesh/
| 2 |  🐆 Anyone in 4D is out 🐆
👉4DAnyone turns a casual monocular video into multi-view videos, enabling downstream 4DGS reconstruction. Full repo under Apache 2.0💙
👉Review https://lnkd.in/p/ec4dzGvb
👉Paper https://arxiv.org/pdf/2608.20335
👉Project https://4danyone.github.io
👉Repo github.com/ant-research/4DAnyone | 1 302 |
| 3 |  🔥🔥UPAL: Unified Points n' Lines🔥🔥
👉ETH (+Microsoft Spatial AI Lab) unveils a novel feature extractor that jointly extracts keypoints, lines, and feature descriptors within a single lightweight net. SOTA in line detection can be achieved by adding only three convolutional layers to existing point extractor. Repo under Apache💙
👉Review https://lnkd.in/p/eW8j5JZj
👉Paper https://arxiv.org/pdf/2608.19894
👉Repo https://github.com/francois141/upal | 1 642 |
| 4 |  🐠Dual-branch Elasticity ID-Tracking🐠
👉TIDE: tracking dense, homogeneous targets, providing a scalable dual-branch design to accommodate diverse hardware constraints. MIT license💙
👉Review https://t.ly/WEDeY
👉Paper https://arxiv.org/pdf/2607.26412
👉Project https://vranlee.github.io/TIDE/
👉Repo https://github.com/vranlee/TIDE | 4 235 |
| 5 |  🔥Decoder-only Any-to-Any Model🔥
👉MODUS unifies any-to-any multimodal generation with one decoder, two experts, and zero task heads. Impressive work. Repo under Apache💙
👉Review https://t.ly/-2QKT
👉Paper https://lnkd.in/dhfBQGhB
👉Project https://lnkd.in/dPD_ECXk
👉Repo https://lnkd.in/dbDHw24u | 3 861 |
| 6 |  🍿 Dawn of Generative Cinematography 🍿
🟩 #TheOdyssey by Christopher Nolan was shot entirely on IMAX 70mm. It feels almost romantic: massive cameras, film stock, premium lenses, and an obsessive pursuit of the highest possible quality at the moment of capture.
👉 Meanwhile, #AI research is heading in the exact opposite direction.
🟩 A pre-print paper released today, "Camera Anything", demonstrates something that sounded like science fiction just a few years ago: you film a scene once... and then you can virtually reposition the camera anywhere.
👉More https://t.ly/Kd7RV
👉Paper arxiv.org/pdf/2607.24591
👉Project yixuanli98.github.io/cameraanything/
👉Repo github.com/yixuanli98/CameraAnything | 3 728 |
| 7 | 🍿Dawn of Generative Cinematography🍿
🟩 The Odissey by Christopher Nolan was shot entirely on IMAX 70mm. It feels almost romantic: massive cameras, film stock, premium lenses, and an obsessive pursuit of the highest possible quality at the moment of capture.
👉 Meanwhile, #AI research is heading in the exact opposite direction.
🟩 A pre-print paper released today, "Camera Anything", demonstrates something that sounded like science fiction just a few years ago: you film a scene once... and then you can virtually reposition the camera anywhere.
🟩 Want a close-up? A drone shot? A ground-level perspective? A side angle? A cinematic tracking shot? You no longer decide where to place the camera during filming. You decide afterwards.
👉 And this fundamentally changes what cinematography means.
🟩 For more than a century, filmmakers have had to make irreversible decisions on set. Camera placement, focal length, movement, framing, etc. These choices became part of the recorded footage forever.
🟩 A scene becomes a 3D representation that can be "re-shot" endlessly from viewpoints that never physically existed. We simply capture "raw" data from which the final result is reconstructed or customized.
🟩Five years from now, will we still talk about shooting a movie? Or will we simply capture a scene and decide later where the camera should have been?
The irony is fascinating. While Nolan reminds us how extraordinary a 70mm camera can be, AI is quietly suggesting that, soon, the camera itself will be optional.
👉The first step towards the generative cinematography.
#deeplearning #computervision #AIwithPapers
👉Discussion https://lnkd.in/dMgakzWm
👉Paper arxiv.org/pdf/2607.24591
👉Project yixuanli98.github.io/cameraanything/
👉Repo github.com/yixuanli98/CameraAnything | 1 |
| 8 | 🍿🍿Dawn of Generative Cinematography🍿🍿
🟩#TheOdyssey by Christopher Nolan was shot entirely on IMAX 70mm. It feels almost romantic: massive cameras, film stock, premium lenses, and an obsessive pursuit of the highest possible quality at the moment of capture.
👉Meanwhile, #AI research is heading in the exact opposite direction.
🟩A pre-print paper released today, "Camera Anything", demonstrates something that sounded like science fiction just a few years ago: you film a scene once... and then you can virtually reposition the camera anywhere.
🟩Want a close-up? A drone shot? A ground-level perspective? A side angle? A cinematic tracking shot? You no longer decide where to place the camera during filming. You decide afterwards.
👉And this fundamentally changes what cinematography means.
🟩For more than a century, filmmakers have had to make irreversible decisions on set. Camera placement, focal length, movement, framing, etc. These choices became part of the recorded footage forever.
🟩A scene becomes a 3D representation that can be "re-shot" endlessly from viewpoints that never physically existed. We simply capture "raw" data from which the final result is reconstructed or customized.
🟩Five years from now, will we still talk about shooting a movie? Or will we simply capture a scene and decide later where the camera should have been?
The irony is fascinating. While Nolan reminds us how extraordinary a 70mm camera can be, AI is quietly suggesting that, soon, the camera itself will be optional.
👉The first step towards the generative cinematography.
#deeplearning #computervision #AIwithPapers
👉Discussion https://lnkd.in/dMgakzWm
👉Paper arxiv.org/pdf/2607.24591
👉Project yixuanli98.github.io/cameraanything/
👉Repo github.com/yixuanli98/CameraAnything | 2 |
| 9 |  🔎MicroZoom at Extreme Scale🔎
👉MicroZoom by UWA synthesizes gigapixel-resolution images grounded in consumer-grade microscope close-ups at magnification levels up to 350×. Impressive. Repo under MIT💙
👉Review https://t.ly/hgJD7
👉Paper https://arxiv.org/pdf/2607.24729
👉Project https://microzoom-sr.github.io/
👉Repo github.com/MicroZoom-SR/MicroZoom-SR.github.io | 2 933 |
| 10 |  💄MagicMakeup Makeup-Transfer💄
👉Makeup-transfer applies the reference makeup to the source face while preserving the source identity. Authors: Zhejiang University & vivo BlueImage Lab. Repo for non commercial💙
👉Review https://t.ly/JYpCr
👉Paper https://arxiv.org/pdf/2607.20924
👉Project https://vivocameraresearch.github.io/magicmakeup/
👉Repo https://github.com/vivoCameraResearch/Magic-Makeup | 2 898 |
| 11 |  💢Unified Video Dense Prediction💢
👉UniD (Adobe Research + Cornell University) is a novel unified video model that jointly predicts: depth, surface normals, semantic segmentation, boundaries, human parts, albedo, shading, and materials. Code TBR💙
👉Review https://t.ly/oo7et
👉Paper https://arxiv.org/pdf/2607.21592
👉Project https://unid-video.github.io/
👉Repo https://github.com/YihongSun/UniD | 3 364 |
| 12 |  🫛Spatially-Aware Class-Agnostic Counting🫛
👉UpCount is reference-free, spatially aware, class-agnostic object counting with an MAE-pretrained ViT, DPT-style feature reassembly, FeatUp-style joint bilateral upsampling, and proposal verification. Repo under MIT💙
👉Review https://t.ly/dWOc3
👉Paper https://arxiv.org/pdf/2607.16826
👉Repo github.com/r28112072-rgb/upcount | 3 443 |
| 13 |  🦜Streaming 4D Transformer🦜
👉IGGT4D is a novel a streaming instance-grounded geometry transformer for online 4D scene understanding. It processes video frames sequentially, reuses historical context through causal spatial-temporal modeling, and incrementally updates a unified representation of camera motion, geometry, and object identity. Repo/Data announced💙
👉Review https://t.ly/LFrKR
👉Paper https://arxiv.org/pdf/2607.19228
👉Project https://iggt4d.github.io/
👉Repo TBA | 3 255 |
| 14 | What about more posts about Robotics? | 3 044 |
| 15 |  👉Not a render. Not a concept. This is GENE.01 by Generative Bionics, the Italians coolest scaleup strikes back: in just six months, they turned GENE.01 into a fully functional humanoid platform that can walk, sense and interact.
👉Full-body multimodal skin perceives touch, proximity, force and temperature, bringing Physical AI closer to safe and natural collaboration with people.
👉More: https://t.ly/F3I3A | 2 988 |
| 16 |  🏯SOTA Music-to-Dance Gen🏯
👉The Tongyi Lab unveils Wan-Dancer, a novel stable minute-scale synthesis at 720p/30fps across five dance genres. Impressive results, new SOTA on long clip by a large margin. Repo under Apache 2.0💙
👉Review https://t.ly/AKY5j
👉Paper https://lnkd.in/d_xA7dwb
👉Project https://lnkd.in/dzfnw2h4
👉Repo https://lnkd.in/d-Zj_cTf | 3 700 |
| 17 |  🌈FlowWAM: flow->action prediction🌈
👉FlowWAM is a novel dual-stream diffusion framework that adopts optical flow as a unified, video-native action representation. Repo under Apache💙
👉Review https://t.ly/FmutT
👉Paper https://arxiv.org/abs/2607.13017
👉Project https://flow-wam.github.io/
👉Repo github.com/YixiangChen515/FlowWAM | 3 941 |
| 18 |  🦧 MonkeyOCRv2 is out! 🦧
👉MonkeyOCRv2 is a text-centric visual foundation model that unifies fine-grained text modeling, cross-task representation learning, and cross-lingual generalization in a single encoder. Released for academic research and non-commercial use💙
👉Review https://t.ly/yicEK
👉Paper https://arxiv.org/pdf/2607.11562
👉Repo https://github.com/Yuliang-Liu/MonkeyOCRv2 | 3 887 |
| 19 |  🎂REMIND: long-term MOT re-ID🎂
👉REMIND by CVAR-UPM is a novel online tracker designed for long-term multi-object re-ID of generic indoor objects from monocular RGB, requiring neither camera pose nor depth. Repo under MIT💙
👉Review https://t.ly/AkQoI
👉Paper https://lnkd.in/dm58mkCv
👉Project https://lnkd.in/dZrAZqFe
👉Repo https://lnkd.in/dbidrwxU | 3 589 |
| 20 |  🌔Foundation Global SFM🌔
👉Glob3R is a global SfM-style reconstruction built on 3D foundation models. key idea: explicitly optimize feed-forward geometric predictions. Repo TBA💙
👉Review https://t.ly/Z_4C7
👉Paper https://arxiv.org/pdf/2607.09225
👉Project https://junyuandeng.github.io/Glob3r/
👉Repo TBA | 3 509 |
