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 225 Technologies & Applications7 701...

📈 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 17 144 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 17 144 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.

17 144

Subscribers

+324 hours

-367 days

-18630 days

4 105

Post views

~ 1 17724 hours

~ 1 35348 hours

23.94%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

17 138

💘 3D-aware Blending via Generative NeRF 💘 👉Novel 3D-aware blending method via generative NeRFs 😎Review https://bit.ly/3lBEJA2 😎Paper arxiv.org/pdf/2302.06608.pdf 😎Project blandocs.github.io/blendnerf 😎Code github.com/naver-ai/BlendNeRF

17 138

🥸 MEGANE: Generative Morphable Eyeglass 🥸 👉#META unveils the most advanced #3D compositional morphable AI for eyeglasses (HD geometry/photometric interaction) 😎Review https://bit.ly/3jOWifu 😎Paper arxiv.org/pdf/2302.04868.pdf 😎Project junxuan-li.github.io/megane

17 138

🎃 In-N-Out: 3D-aware OOD video editing 🎃 👉Novel 3D-aware video editing able to manipulate OOD objects (e.g. heavy makeup, accessories) 😎Review https://bit.ly/3jN0CMu 😎Paper arxiv.org/pdf/2302.04871.pdf 😎Project https://in-n-out-3d.github.io

17 138

🧱 LEGO-Net: Objects in Rooms 🧱 👉Transformer-based iterative method for rearrangement of objects in messy rooms 😎Review https://bit.ly/3HR0fs6 😎Paper arxiv.org/pdf/2301.09629.pdf 😎Project ivl.cs.brown.edu/#/projects/lego-net

17 138

🗿DirectMHP: Multi-Head Pose Estimation🗿 👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles 😎Review https://bit.ly/3HJubXg 😎Paper arxiv.org/pdf/2302.01110.pdf 😎Code github.com/hnuzhy/DirectMHP

17 138

🗿DirectMHP: Multi-Head Pose Estimation🗿 👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles

17 138

🌘 Gen-1: next-gen Generative #AI 🌘 👉#Runaway unveils Gen-1: the next step forward for Generative AI. Registration available for beta -> hurry up! 😎Review https://bit.ly/3YqQYh8 😎Project https://research.runwayml.com/gen1

17 138

🦚 MOSE: coMplex video Object SEgmentation 🦚 👉Novel Dataset for VOS is out! SOTA method on DAVIS is only 59.4% on MOSE 😎Review https://bit.ly/40yzSzW 😎Paper arxiv.org/pdf/2302.01872.pdf 😎Project henghuiding.github.io/MOSE/ 😎Code github.com/henghuiding/MOSE-api

17 138

🧩 Text-Guided #3D Texturing 🧩 👉 Text-Guided HQ textures via iterative diffusion-based process 😎Review https://bit.ly/3ldC6Ez 😎Project texturepaper.github.io/TEXTurePaper 😎Code github.com/TEXTurePaper/TEXTurePaper 😎Paper texturepaper.github.io/TEXTurePaper/static/paper.pdf

17 138

🐓 DREAMIX: General Diffusion Video Editors 🐓 👉#Google unveils the first diffusion-based method able to perform text-based motion/appearance editing of general videos 😎Review https://bit.ly/3I3Hq6B 😎Paper arxiv.org/pdf/2302.01329.pdf 😎Project dreamix-video-editing.github.io/

17 138

💧FLOW360: 360° Neural Optical Flow💧 👉 IIT unveils the first perceptually realistic 360° video benchmark dataset + SLOF method for OF tracking 😎Review https://bit.ly/3wMZZoX 😎Paper arxiv.org/pdf/2301.11880.pdf 😎Project https://siamlof.github.io

17 138

🛋️🛋️ 100% Accurated #3D Labeling 🛋️🛋️ 👉#Amazon unveils a novel tool for fine-grained 3D part labeling. Up to 100% accuracy! Paper (only😢) 😎Review https://bit.ly/3kYpQHQ 😎Paper https://arxiv.org/pdf/2301.10460.pdf

17 138

⭐ Mono-STAR: Unified Tracking/Reconstruction ⭐ 👉Real-time 3D unified framework for semantic fusion, tracking, non-rigid deformation, and topological changes 😎Review https://bit.ly/3Dxvxmx 😎Paper arxiv.org/pdf/2301.13244.pdf 😎Project github.com/changhaonan/Mono-STAR-demo

17 138

🚛 Text-driven Video Neural Editing 🚛 👉A novel text-guided video editing with both appearance/shape 😎Review https://bit.ly/3YcfMJO 😎Paper arxiv.org/pdf/2301.13173.pdf 😎Project text-video-edit.github.io/

17 138

🎷Audio-Visual Semantic Segmentation🎷 👉A novel problem in #AI: pixel-level segmentation of objects that produce sound in the image frame 😎Review https://bit.ly/3wFY6dw 😎Paper arxiv.org/pdf/2301.13190.pdf 😎Project opennlplab.github.io/AVSBench 😎Code github.com/OpenNLPLab/AVSBench

17 138

🐦 PhyCV: Physics-inspired Computer Vision 🐦 👉From UCLA, the first Physics-inspired Computer Vision Library 😎Review https://bit.ly/3HEWozI 😎Code github.com/JalaliLabUCLA/phycv 😎Project photonics.ucla.edu/2022/05/12/jalali-lab-open-sources-phycv-a-physics-inspired-computer-vision-library/

17 138

😍 CLIP/GPT3-driven Affective Faces 😍 👉Columbia unveils a novel framework for facial expressions retrieval given the context of the speaker 😎Review https://bit.ly/3HERna0 😎Paper arxiv.org/pdf/2301.10939.pdf 😎Project realtalk.cs.columbia.edu 😎Code github.com/scottgeng00/realtalk

17 138

🔥CutLER: Unsupervised Segmentation 🔥 👉Novel paper by #META on detection & instance segmentation without human annotations 😎Review https://bit.ly/3DlFiUG 😎Paper arxiv.org/pdf/2301.11320.pdf 😎Code github.com/facebookresearch/CutLER 😎Project people.eecs.berkeley.edu/~xdwang/projects/CutLER

17 138

🐕 MAV3D: #3D Video from Text 🐕 👉#META unveils a novel #AI for generating #3D dynamic videos from text 😎Review https://bit.ly/3WPRAvK 😎Paper arxiv.org/pdf/2301.11280.pdf 😎Project make-a-video3d.github.io