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 241 Technologies & Applications7 723...

📈 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 17 142 subscribers, ranking 7 723 in the Technologies & Applications category and 2 241 in the Malaysia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 17 142 subscribers.

According to the latest data from 23 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -190 over the last 30 days and by -2 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 25.09%. Within the first 24 hours after publication, content typically collects 6.86% reactions from the total number of subscribers.
Post reach: On average, each post receives 4 302 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 24 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.

17 142

Subscribers

-224 hours

-367 days

-19030 days

4 302

Post views

~ 1 17724 hours

~ 1 35348 hours

25.09%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

17 142

🦠 Instance-Level Semantics of Cells 🦠 👉TYC: novel dataset for understanding instance-level semantics & motions of cells in microstructures 😎Review https://t.ly/y-4VZ 😎Paper arxiv.org/pdf/2308.12116.pdf 😎Project christophreich1996.github.io/tyc_dataset/ 😎Code github.com/ChristophReich1996/TYC-Dataset 😎Data tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3930

17 142

Hello everybody, a lot of you asked me to open the comments to better enjoy the posts. I want to follow your suggestion, hope this new mood likes you. 🔥 NO SPAM 🔥 NO COMMERCIAL 🔥 NO UNRESPECTFUL MESSAGEs 🧡JUST AI & SCIENCE ⚠️ BAN AT THE FIRST VIOLATION ⚠️

17 142

🕹️ CoDeF: Video Content Deformation Fields 🕹️ 👉Content deformation field is a new type of video representation for video-editing tasks 😎Review https://t.ly/PIVl- 😎Paper arxiv.org/pdf/2308.07926.pdf 😎Project https://qiuyu96.github.io/CoDeF 😎Code https://github.com/qiuyu96/CoDeF

17 142

⚡️Feature Matching at Light Speed⚡️ 👉LightGlue is a lightweight feature matcher with high accuracy and blazing fast inference 😎Review https://t.ly/jkecX 😎Paper arxiv.org/pdf/2306.13643.pdf 😎Code github.com/cvg/LightGlue

17 142

🥎 SportsMOT + MixSort = Sports MOT 🥎 👉Nanjing just released a MOT dataset for sports scenes + the SOTA code/model for tracking (MixSort) 😎Review https://t.ly/NHUxL 😎Paper arxiv.org/pdf/2304.05170.pdf 😎Project deeperaction.github.io/datasets/sportsmot.html 😎Code github.com/MCG-NJU/MixSort

17 142

🛒 Digital Twins for AutoRetail Checkout 🛒 👉From #Nvidia a novel approach for using 3D assets for training 2D detection and tracking model in AutoRetail Checkout 😎Review https://t.ly/Ea7kt 😎Paper arxiv.org/pdf/2308.09708.pdf 😎Code github.com/yorkeyao/Automated-Retail-Checkout

17 142

🌈 Tracking by Persistent Dynamic View Synthesis 🌈 👉Novel simultaneous addressing of dynamic scene novel-view synthesis + 6-DOF tracking of all dense scene elements 😎Review https://t.ly/Bc535 😎Paper arxiv.org/pdf/2308.09713.pdf 😎Project dynamic3dgaussians.github.io 😎Code github.com/JonathonLuiten/Dynamic3DGaussians

17 142

🔥The code is out!🔥 😎 Code https://github.com/NVlabs/neuralangelo

17 142

🐘 Controllable Synthetic Data (extending Image-Net) 🐘 👉#META's PUG, a new generation of interactive environments for representation learning. Extending Image-Net! 😎Review https://t.ly/nCYs0 😎Paper arxiv.org/pdf/2308.03977.pdf 😎Project pug.metademolab.com 😎Code github.com/facebookresearch/PUG

17 142

👩‍🚀 HD Avatar via Text & Pose 👩‍🚀 👉 Generating expressive #3D avatars from nothing but text descriptions & pose guidance 😎Review https://t.ly/wrSMH 😎Paper arxiv.org/pdf/2308.03610.pdf 😎Project avatarverse3d.github.io

17 142

🎨 I-Paint: Interactive Neural Painting 🎨 👉 Novel AI-powered tool to help artists in completing their artworks 😎Review https://t.ly/ELUb0 😎Paper arxiv.org/pdf/2307.16441.pdf 😎Project helia95.github.io/inp-website 😎Supp helia95.github.io/inp-website/supp_mat.html

17 142

🪛 HANDAL: Real-World Manipulable Objects 🪛 👉 #Nvidia unveils HANDAL dataset: category-level object pose and affordance prediction 😎Review https://t.ly/MXZDI 😎Paper arxiv.org/pdf/2308.01477.pdf 😎Dataset https://wenbowen123.github.io/handaldataset/

17 142

🙏 A quick poll for helping me in improving the quality of the contents about #computervision. Please give me a feedback here: https://t.ly/qXb4C Thanks :)

17 142

🎠 Neural Closed-Loop Simulator 🎠 👉A neural sensor simulator that takes a single recorded log captured by a sensor-equipped vehicle and converts it into a realistic closed-loop multi-sensor simulation 😎Review https://t.ly/EcRLc 😎Paper arxiv.org/pdf/2308.01898.pdf 😎Project https://waabi.ai/unisim/

17 142

📸 Computational Burst Photography in App 📸 👉#Google unveils a novel computational burst system to democratize the professional photography via smartphone 😎Review https://t.ly/5ibJX 😎Paper arxiv.org/pdf/2308.01379.pdf 😎Project https://motion-mode.github.io

17 142

👗 Multimodal Neural Designer 👗 👉 Multimodal #AI that can generate novel fashion images conditioned on text, keypoints, and sketches 😎Review https://t.ly/zVk70 😎Paper arxiv.org/pdf/2304.02051.pdf 😎Code github.com/aimagelab/multimodal-garment-designer

17 142

🥬 Consensus-Adaptive RANSAC 🥬 👉A novel RANSAC that learns to explore the parameter space via a novel attention layer 😎Review https://t.ly/eSLmD 😎Paper arxiv.org/pdf/2307.14030.pdf 😎Code github.com/cavalli1234/CA-RANSAC

17 142

🥬 Consensus-Adaptive RANSAC 🥬 👉A novel RANSAC that learns to explore the parameter space via a novel attention layer

17 142

🐧 Tracking Anything in High Quality 🐧 👉Video multi-object segmenter (VMOS) and a mask refiner (MR) to track anything 😎Review https://t.ly/hAvF2 😎Paper arxiv.org/pdf/2307.13974.pdf 😎Code github.com/jiawen-zhu/HQTrack