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 240 Technologies & Applications7 726...

📈 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 17 151 subscribers, ranking 7 726 in the Technologies & Applications category and 2 240 in the Malaysia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 17 151 subscribers.

According to the latest data from 21 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -166 over the last 30 days and by -6 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 23.63%. 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 4 057 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 22 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.

17 151

Subscribers

-624 hours

-277 days

-16630 days

4 057

Post views

~ 1 17724 hours

~ 1 35348 hours

23.63%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

17 151

🌹 Physics-Based 3D Video-Gen 🌹 👉PhysDreamer, a physics-based approach that leverages the object dynamics priors learned by video generation models. It enables realistic 3D interaction with objects 👉Review https://shorturl.at/bivP4 👉Paper https://arxiv.org/pdf/2404.13026.pdf 👉Project https://physdreamer.github.io/ 👉Code github.com/a1600012888/PhysDreamer

17 151

🛞 6Img-to-3D driving scenarios 🛞 👉EPFL (+ Continental) unveils 6Img-to-3D, novel transformer-based encoder-renderer method to create 3D onbounded outdoor driving scenarios with only six pics 👉Review https://shorturl.at/dZ018 👉Paper arxiv.org/pdf/2404.12378.pdf 👉Project 6img-to-3d.github.io/ 👉Code github.com/continental/6Img-to-3D

17 151

🪼 All You Need is SAM (+Flow) 🪼 👉Oxford unveils the new SOTA for moving object segmentation via SAM + Optical Flow. Two novel models & Source Code announced 💙 👉Review https://t.ly/ZRYtp 👉Paper https://lnkd.in/d4XqkEGF 👉Repo coming 👉Project https://lnkd.in/dHpmx3FF

17 151

🎲 Articulated Objs from MonoClips 🎲 👉REACTO is the new SOTA to address the challenge of reconstructing general articulated 3D objects from single monocular video 👉Review https://t.ly/REuM8 👉Paper https://lnkd.in/d6PWagij 👉Project https://lnkd.in/dpg3x4tm 👉Repo https://lnkd.in/dRZWj6_N

17 151

⚽ SoccerNET: Athlete Tracking & ID ⚽ 👉SoccerNet Challenge is a novel high level computer vision task that is specific to sports analytics. It aims at recognizing the state of a sport game, i.e., identifying and localizing all sports individuals (players, referees, ..) on the field. 👉Review https://t.ly/Mdu9s 👉Paper arxiv.org/pdf/2404.11335.pdf 👉Code github.com/SoccerNet/sn-gamestate

17 151

🧤Neural MusculoSkeletal-MANO🧤 👉SJTU unveils MusculoSkeletal-MANO, novel musculoskeletal system with a learnable parametric hand model. Source Code announced 💙 👉Review https://lnkd.in/dMgakzWm 👉Paper arxiv.org/pdf/2404.10227.pdf 👉Project https://ms-mano.robotflow.ai/ 👉Code announced (no repo yet)

17 151

🪐YOLO-CIANNA: Neural Astro🪐 👉 CIANNA is a general-purpose deep learning framework for (but not only for) astronomical data analysis. Source Code released 💙 👉Review https://t.ly/441XS 👉Paper arxiv.org/pdf/2402.05925.pdf 👉Code github.com/Deyht/CIANNA 👉Wiki github.com/Deyht/CIANNA/wiki

17 151

☄️ Tracking Any 2D Pixels in 3D ☄️ 👉 SpatialTracker lifts 2D pixels to 3D using monocular depth, represents the 3D content of each frame efficiently using a triplane representation, and performs iterative updates using a transformer to estimate 3D trajectories. 👉Review https://t.ly/B28Cj 👉Paper https://lnkd.in/d8ers_nm 👉Project https://lnkd.in/deHjtZuE 👉Code https://lnkd.in/dMe3TvFT

17 151

⚛️ Flying w/ Photons: Neural Render ⚛️ 👉Novel neural rendering technique that seeks to synthesize videos of light propagating through a scene from novel, moving camera viewpoints. Pico-Seconds time resolution! 👉Review https://t.ly/ZqL3a 👉Paper arxiv.org/pdf/2404.06493.pdf 👉Project anaghmalik.com/FlyingWithPhotons/ 👉Code github.com/anaghmalik/FlyingWithPhotons

17 151

🧞 XComposer2: 4K Vision-Language 🧞 👉InternLMXComposer2-4KHD brings LVLM resolution capabilities up to 4K HD (3840×1600) and beyond. Authors: Shanghai AI Lab, CUHK, SenseTime & Tsinghua. Source Code & Models released 💙 👉Review https://t.ly/GCHsz 👉Paper arxiv.org/pdf/2404.06512.pdf 👉Code github.com/InternLM/InternLM-XComposer

17 151

🧞🧞 XComposer2-4K: 4K Vision-Language 🧞🧞 👉InternLMXComposer2-4KHD brings LVLM resolution capabilities up to 4K HD (3840×1600) and beyond. Authors: Shanghai AI Lab, CUHK, SenseTime & Tsinghua. Source Code & Models released 💙 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Large Vision-Language Models (LVLMs) to 4K HD ✅Free-form Interleaved Text-Image Composition ✅Dynamic Resolution / Automatic Patch Config. ✅SOTA or competitive despite only 7B params #artificialintelligence #machinelearning #ml #AI #deeplearning #computervision #AIwithPapers #metaverse 👉Discussion https://lnkd.in/dMgakzWm 👉Paper https://arxiv.org/pdf/2404.06512.pdf 👉Code github.com/InternLM/InternLM-XComposer

17 151

🔌 BodyMAP: human body & pressure 🔌 👉#Nvidia (+CMU) unveils BodyMAP, the new SOTA in predicting body mesh (3D pose & shape) and 3D applied pressure on the human body. Source Code released, Dataset coming 💙 👉Review https://t.ly/8926S 👉Project bodymap3d.github.io/ 👉Paper https://lnkd.in/gCxH4ev3 👉Code https://lnkd.in/gaifdy3q

17 151

👗 Neural Bodies with Clothes 👗 👉Neural-ABC is a novel parametric model based on neural implicit functions that can represent clothed human bodies with disentangled latent spaces for identity, clothing, shape, and pose. Author: University of Science & Technology of China. Dataset & Source Code released 💙 👉Review https://t.ly/Un1wc 👉Project https://lnkd.in/dhDG6FF5 👉Paper https://lnkd.in/dhcfK7jZ 👉Code https://lnkd.in/dQvXWysP

17 151

👆 iSeg: Interactive 3D Segmentation 👆 👉 iSeg: interactive segmentation technique for 3D shapes operating entirely in 3D. It accepts both positive/negative clicks directly on the shape's surface, indicating inclusion & exclusion of regions. 👉Review https://t.ly/tyFnD 👉Paper https://lnkd.in/dydAz8zp 👉Project https://lnkd.in/de-h6SRi 👉Code (coming)

17 151

🕷️ Gen-NeRF2NeRF Translation 🕷️ 👉GenN2N: unified NeRF-to-NeRF translation for editing tasks such as text-driven NeRF editing, colorization, super-resolution, inpainting, etc. 👉Review https://t.ly/VMWAH 👉Paper https://arxiv.org/pdf/2404.02788.pdf 👉Project https://xiangyueliu.github.io/GenN2N/ 👉Code https://github.com/Lxiangyue/GenN2N

17 151

🔥🔥Code is out 🔥🔥 https://github.com/AssafSinger94/dino-tracker

17 151

🔥 ECoDepth: SOTA Diffusive Mono-Depth 🔥 👉New SIDE model using a diffusion backbone conditioned on ViT embeddings. It's the new SOTA in SIDE. Source Code released 💙 👉Review https://t.ly/s2pbB 👉Paper https://lnkd.in/eYt5yr_q 👉Code https://lnkd.in/eEcyPQcd

17 151

🔘 RELI11D: Multimodal Humans 🔘 👉RELI11D is the ultimate and high-quality multimodal human motion dataset involving LiDAR, IMU system, RGB camera, and Event camera. Dataset & Source Code to be released soon💙 👉Review https://t.ly/5EG6X 👉Paper https://lnkd.in/ep6Utcik 👉Project https://lnkd.in/eDhNHYBb

17 151

🪼 Universal Mono Metric Depth 🪼 👉ETH unveils UniDepth: metric 3D scenes from solely single images across domains. A novel, universal and flexible MMDE solution. Source code released💙 👉Review https://t.ly/5C8eq 👉Paper arxiv.org/pdf/2403.18913.pdf 👉Code github.com/lpiccinelli-eth/unidepth

17 151

🪼 Universal Mono Metric Depth 🪼 👉ETH unveils UniDepth: metric 3D scenes from solely single images across domains. A novel, universal and flexible MMDE solution. Source code released💙 👉Review https://t.ly/5C8eq 👉Paper https://arxiv.org/pdf/2403.18913.pdf 👉Code https://github.com/lpiccinelli-eth/unidepth