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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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📈 Analytical overview of Telegram channel AI with Papers - Artificial Intelligence & Deep Learning

Channel AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) in the English language segment is an active participant. Currently, the community unites 17 260 subscribers, ranking 7 543 in the Technologies & Applications category and 2 150 in the Malaysia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 17 260 subscribers.

According to the latest data from 28 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 229 over the last 30 days and by 1 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 17.18%. Within the first 24 hours after publication, content typically collects 7.02% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 965 views. Within the first day, a publication typically gains 1 211 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 15.
  • Thematic interests: Content is focused on key topics such as framework, object, dataset, tba, depth.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“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”

Thanks to the high frequency of updates (latest data received on 29 October, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

17 260
Subscribers
+124 hours
+17 days
+22930 days
Posts Archive
🪁 VoxFormer: 2D->#3D Voxel Transformer 🪁 👉#Nvidia VoxFormer: transformer for #3D volumetric semantics from 2D images 😎Paper arxiv.org/pdf/2302.12251.pdf 😎Code github.com/NVlabs/VoxFormer

🫳 Neural Relighting of Hands 🫴 👉#META unveil the first neural relighting for personalized hands in real-time under novel illumination 😎Review https://bit.ly/3SblmKC 😎Paper arxiv.org/pdf/2302.04866.pdf 😎Project sh8.io/#/relightable_hands

🏀 #NBA Mixed Reality is NUTS 🏀 👉The premiere of the streaming app of the #NBA is totally INSANE. A mix of #AI, CG and much
🏀 #NBA Mixed Reality is NUTS 🏀 👉The premiere of the streaming app of the #NBA is totally INSANE. A mix of #AI, CG and much more👇 🏀More: https://bit.ly/3IJ3uUp

🛡️ TPV: Tesla's O-Net competitor 🛡️ 👉From Beijing an open-source approach for vision-centric autonomous driving #3D perception 😎Review https://bit.ly/3lNvVYc 😎Paper arxiv.org/pdf/2302.07817.pdf 😎Code github.com/wzzheng/TPVFormer

🌶️ 3D-aware conditional generative AI 🌶️ 👉 Pix2Pix3D: 3D-aware conditional generative AI for controllable photorealistic synthesis 😎Review https://bit.ly/3I80MWS 😎Paper arxiv.org/pdf/2302.08509.pdf 😎Project www.cs.cmu.edu/~pix2pix3D 😎Code github.com/dunbar12138/pix2pix3D

🦩 One-Shot Face via LSs of StyleGAN2 🦩 👉 Novel video generation framework with edits, facial motions, deformations & identity 😎Review https://bit.ly/3xuChhF 😎Paper arxiv.org/pdf/2302.07848.pdf 😎Project trevineoorloff.github.io/FaceVideoReenactment_HybridLatents.io/

📬 DIVOTrack: crossview MOT dataset 📬 👉 DIVOTrack + CrossMOT: the ultimate solution for MOT in realistic scenario 😎Review https://bit.ly/3YSFZgL 😎Paper arxiv.org/pdf/2302.07676.pdf 😎Code github.com/shengyuhao/DIVOTrack

🦞 SOTA ALERT: YOWOv2 is out! 🦞 👉 The 2nd-gen of YOWO, real-time detection of spatio-temporal action 😎Review https://bit.ly/3IscY60 😎Paper arxiv.org/pdf/2302.06848v1.pdf 😎Code github.com/yjh0410/YOWOv2

🌅 Novel semantics-guided natural synthesis 🌅 👉Alibaba #AI unveils a novel semantics-guided view synthesis of natural scenes 😎Review https://bit.ly/4115MVJ 😎Paper arxiv.org/pdf/2302.07224.pdf 😎Project zju3dv.github.io/paintingnature

🌅 Novel semantics-guided natural synthesis 🌅 👉Alibaba #AI unveils a novel semantics-guided view synthesis of natural scenes

💘 3D-aware Blending via Generative NeRF 💘 👉Novel 3D-aware blending method via generative NeRFs 😎Review https://bit.ly/3lBEJA2 😎Paper arxiv.org/pdf/2302.06608.pdf 😎Project blandocs.github.io/blendnerf 😎Code github.com/naver-ai/BlendNeRF

🥸 MEGANE: Generative Morphable Eyeglass 🥸 👉#META unveils the most advanced #3D compositional morphable AI for eyeglasses (HD geometry/photometric interaction) 😎Review https://bit.ly/3jOWifu 😎Paper arxiv.org/pdf/2302.04868.pdf 😎Project junxuan-li.github.io/megane

🎃 In-N-Out: 3D-aware OOD video editing 🎃 👉Novel 3D-aware video editing able to manipulate OOD objects (e.g. heavy makeup, accessories) 😎Review https://bit.ly/3jN0CMu 😎Paper arxiv.org/pdf/2302.04871.pdf 😎Project https://in-n-out-3d.github.io

🧱 LEGO-Net: Objects in Rooms 🧱 👉Transformer-based iterative method for rearrangement of objects in messy rooms 😎Review https://bit.ly/3HR0fs6 😎Paper arxiv.org/pdf/2301.09629.pdf 😎Project ivl.cs.brown.edu/#/projects/lego-net

🗿DirectMHP: Multi-Head Pose Estimation🗿 👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles 😎Review https://bit.ly/3HJubXg 😎Paper arxiv.org/pdf/2302.01110.pdf 😎Code github.com/hnuzhy/DirectMHP

🗿DirectMHP: Multi-Head Pose Estimation🗿 👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles 😎Review https://bit.ly/3HJubXg 😎Paper arxiv.org/pdf/2302.01110.pdf 😎Code github.com/hnuzhy/DirectMHP

🗿DirectMHP: Multi-Head Pose Estimation🗿 👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles

🌘 Gen-1: next-gen Generative #AI 🌘 👉#Runaway unveils Gen-1: the next step forward for Generative AI. Registration available for beta -> hurry up! 😎Review https://bit.ly/3YqQYh8 😎Project https://research.runwayml.com/gen1

🦚 MOSE: coMplex video Object SEgmentation 🦚 👉Novel Dataset for VOS is out! SOTA method on DAVIS is only 59.4% on MOSE 😎Review https://bit.ly/40yzSzW 😎Paper arxiv.org/pdf/2302.01872.pdf 😎Project henghuiding.github.io/MOSE/ 😎Code github.com/henghuiding/MOSE-api

🧩 Text-Guided #3D Texturing 🧩 👉 Text-Guided HQ textures via iterative diffusion-based process 😎Review https://bit.ly/3ldC6Ez 😎Project texturepaper.github.io/TEXTurePaper 😎Code github.com/TEXTurePaper/TEXTurePaper 😎Paper texturepaper.github.io/TEXTurePaper/static/paper.pdf