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

Malaysia2 235 Technologies & Applications7 702...

📈 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 17 145 subscribers, ranking 7 702 in the Technologies & Applications category and 2 235 in the Malaysia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 17 145 subscribers.

According to the latest data from 24 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -197 over the last 30 days and by -7 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 25.73%. Within the first 24 hours after publication, content typically collects 6.87% reactions from the total number of subscribers.
Post reach: On average, each post receives 4 411 views. Within the first day, a publication typically gains 1 177 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 26.
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 25 June, 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.

17 145

Subscribers

-724 hours

-427 days

-19730 days

4 411

Post views

~ 1 17724 hours

~ 1 35348 hours

25.73%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

17 144

💎 Clothes-Changing Re-Identification 💎 👉The new SOTA in wild Re-identification by mixing appearance & face features 😎Review https://bit.ly/3HdTTUU 😎Paper arxiv.org/pdf/2211.13807.pdf 😎Project www.vision.huji.ac.il/reface 😎Code github.com/bar371/ReFace

17 144

👽HD Faces via "Hacked" Smartphone👽 👉A novel method for HD faces from (polarizing-foils) smartphones 😎Review https://bit.ly/3H8yhJN 😎Paper arxiv.org/pdf/2212.01160.pdf 😎Project dazinovic.github.io/polface

17 144

🫐 Tracking EVERYTHING in the wild 🫐 👉Disentangling classification from tracking, Track Every Thing Accuracy (TETA) for SOTA 😎Review https://bit.ly/3F2rfU7 😎Paper arxiv.org/pdf/2207.12978.pdf 😎Project www.vis.xyz/pub/tet/

17 144

🎨 Dr.3D: adapting 3D GANs to Arts 🎨 👉Novel 3D GAN domain adaptation method for drawings. From portraits to 3D! 😎Review https://bit.ly/3He3Phv 😎Paper arxiv.org/pdf/2211.16798.pdf 😎Project jinwonjoon.github.io/dr3d/ 😎Code github.com/JinWonjoon/Dr.3D

17 144

Comments: https://bit.ly/3B6T6S9

17 144

Should I write a book (no technicalities, for everyone) about the evolution of the modern Computer Vision / AI ?

Anonymous voting

17 144

🤪 Just another ORDINARY week in #AI community 🤪 😈 Let's talk -> https://bit.ly/3VsEfth 😈 Invite friends -> https://t.me/AI_DeepLearning

17 144

💎 SJC: from 2D -> #3D generation 💎 👉 Novel method to convert pretrained 2D diffusion into 3D generative mode 😎Review https://bit.ly/3UppHJx 😎Paper arxiv.org/pdf/2212.00774.pdf 😎Code github.com/pals-ttic/sjc 😎Project pals.ttic.edu/p/score-jacobian-chaining

17 144

🔥🔥 #StableDiffusion2 paper is out! 🔥🔥 👉The progress with #StableDiffusion at #neurips2022 conference. Crazy times! 😎Review https://bit.ly/3ESo5Cn 😎Paper arxiv.org/pdf/2210.03142.pdf

17 144

🔥#AIwithPapers: we are 5,200+!🔥 👉 Me (and you, all), these days (audio ON!) 🤣 😈 Share -> https://bit.ly/3fA5geu 😈 Invite friends -> https://t.me/AI_DeepLearning

17 144

🔥#AIwithPapers: we are 5,200+!🔥 👉 Me (and you, all), these days (audio ON!) 🤣 😈 Share -> https://bit.ly/3fA5geu 😈 Invite friends -> https://t.me/AI_DeepLearning

17 144

🧨Fast-SNARF: 150× faster Neural Fields🧨 👉Voxel-based correspondence, pre-computed skinning, and #cuda kernels -> avatar 150x faster! 😎Review https://bit.ly/3OMvEPo 😎Code github.com/xuchen-ethz/fast-snarf 😎Paper dataset.ait.ethz.ch/downloads/fast-snarf/paper.pdf

17 144

🚗 3DDesigner: Text-guided Diffusion 🚗 👉Novel method to generate #3D fine-grained objects via textual diffusion 😎Review https://bit.ly/3Fbmyc1 😎Project 3ddesigner-diffusion.github.io/ 😎Paper arxiv.org/pdf/2211.14108.pdf

17 144

💡Diffusive Generation/Inpainting/Reconstruction💡 👉The first 3D-aware diffusion model purely trained from 2D images only 😎Review https://bit.ly/3XyHyjY 😎Paper arxiv.org/pdf/2211.09869.pdf 😎Code github.com/Anciukevicius/RenderDiffusion

17 144

🐈 SpaText: Spatio-Textual Generation 🐈 👉#META AI unveils a novel text-to-image generation using open-vocabulary scene control 😎Review https://bit.ly/3OKcdXz 😎Project pnp-diffusion.github.io/ 😎Paper arxiv.org/pdf/2211.14305.pdf 😎Code (coming)

17 144

🥬 Diffusive Sketch-Guided Text-to-Image 🥬 👉#Google unveils a universal approach for T2I (pre-trained) diffusion: free-hand, saliency-guided, etc. 😎Review https://bit.ly/3XFVMj2 😎Project sketch-guided-diffusion.github.io/ 😎Paper sketch-guided-diffusion.github.io/files/sketch-guided-preprint.pdf

17 144

💃EDGE: Diffusive Dancers Generator💃 👉New SOTA in editable human-dancer generation according to the input music 😎Review https://bit.ly/3u2egfY 😎Paper arxiv.org/pdf/2211.10658.pdf 😎Project edge-dance.github.io/

17 144

🍫 Tracking in Motion-Blurred Clips 🍫 👉Robust line segment detector in motion-blurred clips -> #SLAM / #3D. 😎Review https://bit.ly/3F2wHrb 😎Paper arxiv.org/pdf/2211.07365.pdf 😎Project levenberg.github.io/FE-LSD/ 😎Code github.com/lh9171338/FE-LSD

17 144

🔥🔥 UPDATE 🔥🔥 Code Released: https://bit.ly/3tZLWuP

17 144

🥇MineDojo: Agents at Internet-Scale🥇 👉The #neurips2022 Outstanding Paper Award winner is out. By #Nvidia et al. 😎Review https://bit.ly/3F0RPhN 😎Project https://minedojo.org/ 😎Paper arxiv.org/pdf/2206.08853.pdf 😎Code github.com/MineDojo/MineDojo