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

🔥New SOTA in Panoptic Segmentation🔥 👉#Google (with Hinton🤯) unveils Pix2Seq-D: novel generalist framework for panoptic segmentation 😎Review https://bit.ly/3DmpbGM 😎Paper arxiv.org/pdf/2210.06366.pdf

17 144

🦙LaMAR: Localization/Mapping for #AR🦙 👉A new benchmark for #AR in large and unconstrained scenes 😎Review https://bit.ly/3DjlnWU 😎Paper lamar.ethz.ch/files/LaMAR.pdf 😎Project https://lamar.ethz.ch/ 😎Code github.com/microsoft/lamar-benchmark

17 144

🪂 Parallel NeRF for 6-DoF pose 🪂 👉#Nvidia unveils a parallel NeRF for 6-DoF target pose estimation 😎Review https://bit.ly/3guWWwA 😎Paper arxiv.org/pdf/2210.10108.pdf 😎Project https://pnerfp.github.io/

17 144

🔥Meta Omni3D: code is out!🔥 👉Source Code, models, and data just released by #META ! 😎Review https://bit.ly/3MIWxD9 😎Paper arxiv.org/pdf/2207.10660.pdf 😎Project garrickbrazil.com/omni3d/ 😎Code github.com/facebookresearch/omni3d

17 144

🔥 Dressing Avatars by #META 🔥 👉Novel deep photorealistic appearance method for physically-simulated clothing in #metaverse 😎Review https://bit.ly/3yRBW9Y 😎Paper arxiv.org/pdf/2206.15470.pdf

17 144

⚽Markerless Body-Object Interaction⚽ 👉Novel whole-bodies/objects interaction method from multi-view RGB-D data 😎Review https://bit.ly/3yO56GY 😎Data intercap.is.tue.mpg.de/login.php 😎Project https://intercap.is.tue.mpg.de 😎Code github.com/YinghaoHuang91 😎Paper intercap.is.tue.mpg.de/media/upload/main.pdf

17 144

⛽ Stable Diffusion in #Blender ⛽ 👉Render with SuperPowers: novel scene render via text prompt 😎Review https://bit.ly/3s1mEeN 😎Code github.com/benrugg/AI-Render

17 144

🪲#6D estimation fully in the wild🪲 👉First ever self-supervised 6D pose estimation training in the wild 😎Review https://bit.ly/3yHdHuS 😎Paper arxiv.org/pdf/2210.07199.pdf 😎Project kywind.github.io/self-pose 😎Code (soon)

17 144

🧮 Novel DM for 3D Shapes by #Nvidia 🧮 👉Hierarchical Latent Point Diffusion Model (LION) for 3D shape generation 😎Review https://bit.ly/3yDhZ6I 😎Paper arxiv.org/pdf/2210.06978.pdf 😎Project https://nv-tlabs.github.io/LION/ 😎Code(soon) github.com/nv-tlabs/LION

17 144

🦑 Instant Map-free Relocalization 🦑 👉#Niantic unveils a novel instant, metric scaled re-localization with one single photo 😎Review https://bit.ly/3S1Gdyh 😎Paper arxiv.org/pdf/2210.05494.pdf 😎Project research.nianticlabs.com/mapfree-reloc-benchmark 😎Data research.nianticlabs.com/mapfree-reloc-benchmark/dataset

17 144

🔥 Matterport 3D Semantics Dataset 🔥 👉#Meta opens HM3DSEM, the largest #3D real-world dataset with dense semantic 😎Review https://bit.ly/3yF4W4G 😎Paper arxiv.org/pdf/2210.05633.pdf 😎Project aihabitat.org/datasets/hm3d-semantics 😎Data github.com/matterport/habitat-matterport-3dresearch

17 144

🥬 "Perception Test" by #DeepMind 🥬 👉Huge dataset with obj & point tracks, temporal sounds, multiple & grounded vQA 😎Review https://bit.ly/3Vqh96Q 😎Dataset github.com/deepmind/perception_test 😎Project www.deepmind.com/blog/measuring-perception-in-ai-models

17 144

🏅GENIE by #Nvidia -> Faster Generation🏅 👉Higher-Order Denoising Diffusion Solvers for faster and better synthesis 😎Review https://bit.ly/3CRjtwr 😎Project nv-tlabs.github.io/GENIE/ 😎Paper arxiv.org/pdf/2210.05475.pdf 😎Code github.com/nv-tlabs/GENIE

17 144

🍏 f-DM: Diffusion Models by Apple 🍏 👉Spectacular work by #Apple on DMs: HQ generation with better efficiency and semantic 😎Review https://bit.ly/3Tils2u 😎Project https://jiataogu.me/fdm/ 😎Paper arxiv.org/pdf/2210.04955.pdf

17 144

🥏 EVA3D: new SOTA in #3D humans 🥏 👉EVA3D: new SOTA for unconditional NeRF-human generation from 2D only 😎Review https://bit.ly/3Th9qX7 😎Code github.com/hongfz16/EVA3D 😎Paper arxiv.org/pdf/2210.04888.pdf 😎Project hongfz16.github.io/projects/EVA3D.html

17 144

🔥SIMPLI: ligh novel-view synthesis🔥 👉Lightweight novel-view synthesis by #Samsung for arbitrary forward-facing scenes 😎Review https://bit.ly/3CivSYZ 😎Project samsunglabs.github.io/MLI 😎Code github.com/SamsungLabs/MLI 😎Paper samsunglabs.github.io/MLI/paper/paper.pdf

17 144

🍋 Long Video via Transformers 🍋 👉TECO is a vector-quantized latent dynamics prediction for long video 😎Review https://bit.ly/3Ch0tWD 😎Project wilson1yan.github.io/teco/ 😎Paper arxiv.org/pdf/2210.02396.pdf 😎Code github.com/wilson1yan/teco

17 144

🔥 #AIwithPapers: we are 4,500+! 🔥 💙💛 Someone put the smiling 💩 under a few recent posts. But I still love you! 💙💛 😈 Invite your friends -> https://t.me/AI_DeepLearning

17 144

⚛️SOTA ALERT! Particles Tracking ⚛️ 👉The new SOTA in video particles tracking. "Old school" taste, with neural flavor 🧡 😎Review https://bit.ly/3CaU5Ai 😎Project particle-video-revisited.github.io/ 😎Paper arxiv.org/pdf/2204.04153.pdf 😎Code github.com/aharley/pips

17 144

🔥 Human MDM: source code is out! 🔥 👉A classifier-free diffusion-based generative model for human motion domain 😎Review https://bit.ly/3rFhR2G 😎Project guytevet.github.io/mdm-page 😎Paper arxiv.org/pdf/2209.14916.pdf 😎Code github.com/GuyTevet/motion-diffusion-model