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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 17 136 subscribers, ranking 7 701 in the Technologies & Applications category and 2 225 in the Malaysia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 17 136 subscribers.

According to the latest data from 25 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -186 over the last 30 days and by 3 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 23.94%. 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 0 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 0.
  • 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 26 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.

17 136
Subscribers
+324 hours
-367 days
-18630 days
Posts Archive
🦑Big Egocentric Dataset by #Meta 🦑 👉Novel dataset to speed-up research on egocentric MR/AI 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅159 sequences, multiple sensors ✅Scenarios: cooking, exercising, etc. ✅‘Desktop Activities’ via multi-view mocap ✅Dataset available upon request More: https://bit.ly/3QDccVW

🐠Largest Dataset for #autonomousdriving🐠 👉SHIFT: largest synthetic dataset for #selfdrivingcars. Shifts in cloud, rain, fog, time of day, vehicle & pedestrian density🤯 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅4,800+ clips, multi-view sensor suite ✅Semantic/instance, M/stereo depth ✅2D/3D object detection, MOT ✅Optical flow, point cloud registration ✅Visual-Odo, trajectory & human pose More: https://bit.ly/3HJBUUT

🍅Segmentation with INSANE Occlusions🍅 👉CMU unveils WALT: segmenting in severe occlusion scenarios. Performance over human. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅WALT: Watch & Learn Time-lapse ✅4K/1080p cams on streets over a year ✅Performance over human-supervised ✅Object-occluder-occluded neural layers ✅Source code under MIT license More: https://bit.ly/3n7pvjO

🔥 #AIwithPapers: we are 2,900+! 🔥 💙💛 Cheers from "Black Metal Lady Gaga" plotted by DallE-mini 💙💛 😈 Invite your friend
🔥 #AIwithPapers: we are 2,900+! 🔥 💙💛 Cheers from "Black Metal Lady Gaga" plotted by DallE-mini 💙💛 😈 Invite your friends -> https://t.me/AI_DeepLearning

✋HaGRID : Half Million Hands👋 👉Russian Sberbank opens HaGRID, enormous dataset for HGR. "Peace" label is present 🔵🟡 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅552,992 samples, 18 classes ✅HD resolution in RGB format ✅BBox, gesture, leading hands ✅Dataset/models available More: https://bit.ly/3n2cd8r

🦕 SAVi++: Segmentation by #Google 🦕 👉Novel unsupervised object-centric #AI to predict depth signals from slot-based video representation 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Segmenting complex dynamic scenes ✅Static/Moving objects on naturalistic BG ✅LiDAR-SAVi: segmenting in the wild ✅Source code and model soon available! More: https://bit.ly/3n3hywd

🧠 Bias in #AI, explained simple 🧠 👉Asking DallE-Mini to help me to show what the BIAS in #AI is 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐞𝐝 𝐒𝐚𝐦𝐩𝐥𝐞𝐬: ✅Best eng.->men/Caucasians ✅Best doctors->men/Caucasians ✅Top CEOs->men/Caucasians ✅Chef, kitchen->men/Caucasians ✅Rich People->only Caucasians ✅Poor People->non-Caucasians ✅Italian engineers->back in 30's ✅Chinese eng.->infrastructures ✅Italian working->local market ✅Chinese working->vegetables ✅Men workers->constructions ✅Women workers->only office More: https://bit.ly/3b0UFqd

🏄🏻‍♀️Neural Super-Resolution in Movies🏄🏻‍♀️ 👉Implicit neural representation to get arbitrary spatial resolution & FPS -> Super Resolution! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Video as continuous video representation ✅Clips in arbitrary space/time resolution ✅OOD generalization in space-time ✅Source code and models available More: https://bit.ly/3xsqccf

🐹 NOAH just open-sourced! 🐹 👉A novel approach to find the optimal design of prompt modules through NAS algos. 𝐇𝐢𝐠𝐡𝐥𝐢
🐹 NOAH just open-sourced! 🐹 👉A novel approach to find the optimal design of prompt modules through NAS algos. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅NOAH from Neural prOmpt seArcH ✅Parameter-efficient “prompt modules” ✅Efficient NAS-based implementation ✅Better than transfer, few-shot & domain gen. More: https://bit.ly/3MKfVhi

👗BodyMap: Hyper-Detailed Humans👗 👉#META unveils 1st-ever dense continuous correspondence for clothed humans 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅1st-ever dense continuous corresp. ✅HQ fingers, hair, and clothes ✅Novel ViT-based architecture ✅SOTA on DensePose COCO More: https://bit.ly/39nEPps

🧨 Scaling Transformers to GigaPixels!🧨 👉Novel ViT called Hierarchical Image Pyramid Transformer (HIPT) -> Scaling to GigaPixels! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Gigapixel whole-slide imaging (WSI) ✅Leveraging natural hier. structure of WSI ✅Self-supervised Hi-Res representations ✅Source code and models available! More: https://bit.ly/3xLuzkg

🔥One Millisecond Backbone. Fire!🔥 👉MobileOne by #Apple: efficient mobile backbone with inference <1 ms on #iPhone12! 𝐇
🔥One Millisecond Backbone. Fire!🔥 👉MobileOne by #Apple: efficient mobile backbone with inference <1 ms on #iPhone12! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅75.9% top-1 accuracy on ImageNet ✅38× faster than MobileFormer net ✅Classification, detection & segmentation ✅Source code & model soon available! More: https://bit.ly/3tsT7f2

🎒 EG3D: source code is out! 🎒 👉#Nvidia just opened EG3D: real time multi-view faces w/ HQ #3D geometry! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Tri-plane-based 3D GAN framework ✅Pose-correlated attribute (expression) ✅SOTA in uncond. 3D-aware synthesis ✅Source code & models NOW available! More: https://bit.ly/3aOfHs0

🏖️ HumanNeRF: source code is out! 🏖️ 👉Pausing the video at any frame and rendering the subject from arbitrary views! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Synthesizing photorealistic humans ✅Synthesizing details, ie. cloth & face ✅Volumetric canonical T-pose ✅Skeletal rigid/non-rigid decomposition More: https://bit.ly/3NEkTNY

⚽ Zero to #Messi with #deeplearning ⚽ 👉EA unveils a neural system to learn multiple soccer juggling skills 😍 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Learning difficult soccer juggling skills ✅Layer-wise mixture-of-experts architecture ✅Specialization arises naturally ✅Adaptive random walk training strategy More: https://bit.ly/3mwRaL2

🏇🏻Neural Clips by #Nvidia: INSANE 🏇🏻 👉Neural generation with changes in camera viewpoint & content that arises over time 🤯 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Novel hierarchical generator architecture ✅Temp. receptive field + temporal embed. ✅Multi-res. with super-resolution network ✅SOTA in long clip with motion & changes ✅Code, data & models in August 2022 🏖️ More: https://bit.ly/3zroWsC

🍏 Open Source Vision from #Apple 🍏 👉CVNets: open-source (not a joke) lib for neural vision. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅PyTorch
🍏 Open Source Vision from #Apple 🍏 👉CVNets: open-source (not a joke) lib for neural vision. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅PyTorch-based neural lib. for vision ✅Train 2−4× longer w/ augmentations ✅Plug-and-play components for CV ✅Source code under a custom license More: https://bit.ly/39d1dSj

🔴 Geogram: geometric algos in C++ 🔴 👉Novel open-source programming library with (research) geometric algorithms in C++ 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Geometry Processing from #INRIA ✅30+ papers from SIGGRAPH, etc. ✅Grants: GOODSHAPE & VORPALINE ✅Code (mostly C++) under BSD 3 More: https://bit.ly/3mhS4L7

🧘🏻‍♂️YogNet: neural yoga assistant🧘🏻‍♂️ 👉Multi-person yoga neural expert for 20 asanas 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅CNNs & reg
🧘🏻‍♂️YogNet: neural yoga assistant🧘🏻‍♂️ 👉Multi-person yoga neural expert for 20 asanas 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅CNNs & reg.LSTMs + 3D-CNNs ✅Multi-person asanas in real-time ✅YAR: dataset for yoga & posture ✅1206 videos, 2D RGB camera More: https://bit.ly/3NncVbE

🐢 Transformer-Based Sens-Fusion 🐢 👉Updating TransFuser (CVPR21): image + LiDAR representations with self-attention 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Existing approach can't handle traffic 😢 ✅Novel multi-modal fusion transformer ✅The new SOTA in driving performance ✅Reducing avg collisions per KM by 48% ✅Insights on current limitations of E2E More: https://bit.ly/391dmd6