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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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📈 Análisis del canal de Telegram AI with Papers - Artificial Intelligence & Deep Learning

El canal AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 17 145 suscriptores, ocupando la posición 7 702 en la categoría Tecnologías y Aplicaciones y el puesto 2 235 en la región Malasia.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 17 145 suscriptores.

Según los últimos datos del 24 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -197, y en las últimas 24 horas de -7, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 25.73%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 6.87% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 4 411 visualizaciones. En el primer día suele acumular 1 177 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 26.
  • Intereses temáticos: El contenido se centra en temas clave como framework, object, dataset, tba, depth.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
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

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 25 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.

17 145
Suscriptores
-724 horas
-427 días
-19730 días
Archivo de publicaciones
🔥 Stable Diffusion 2.0 is out! 🔥 👉The open-source of #StableDiffusion V2 just released. Magic 🤯 😎Review https://bit.ly/3XwGInO 😎Code github.com/Stability-AI/stablediffusion 😎Blog stability.ai/blog/stable-diffusion-v2-release

🍹 Perceptual NeRF-Inpainting 🍹 👉A novel complete process for #3D scene manipulation powered by NeRF 😎Review https://bit.ly/3Vn0EaT 😎Paper arxiv.org/pdf/2211.12254.pdf 😎Project spinnerf3d.github.io

🖌️ Neural Semantic Image Synthesis 🖌️ 👉Adobe unveils SceneComposer: text to 2D semantic canvas with precise shapes 😎Review https://bit.ly/3EtDyIL 😎Project zengyu.me/scenec 😎Paper arxiv.org/pdf/2211.11742.pdf 😎Code github.com/zengxianyu/scenec

🔥🔥 "There can be only one" 🔥🔥 👉#Catfighting from the #AI community 😂 😎Review https://bit.ly/3Ax5I4n
🔥🔥 "There can be only one" 🔥🔥 👉#Catfighting from the #AI community 😂 😎Review https://bit.ly/3Ax5I4n

🧟‍♀️ Generative Neural Texture for Avatars 🧟‍♀️ 👉Novel #3D GAN for (the most, ever) detailed facial avatars from unstructured 2D images 😎Review https://bit.ly/3EvF0dS 😎Project mrtornado24.github.io/Next3D/ 😎Paper arxiv.org/pdf/2211.11208.pdf 😎Code github.com/MrTornado24/Next3D

🔥🔥MagicVideo: Text-To-Video #AI🔥🔥 👉MagicVideo: novel efficient text-to-video AI based on latent diffusion models 😎Review https://bit.ly/3UX5YCd 😎Paper arxiv.org/pdf/2211.11018.pdf 😎Project magicvideo.github.io/

🎴VideoINR: Neural Video Super-Resolution🎴 👉VideoINR: the new SOTA in Continuous Space-Time Super-Resolution is out! 😎Review https://bit.ly/3gpeudY 😎Paper arxiv.org/pdf/2206.04647.pdf 😎Project zeyuan-chen.com/VideoINR 😎Code github.com/Picsart-AI-Research/VideoINR-Continuous-Space-Time-Super-Resolution

🔥Perfect Human Annotation by Google!🔥 👉TAP-Vid dataset: accurate human annotations + synthetic videos with PERFECT ground-truth 😎Review https://bit.ly/3i1KRzZ 😎Code github.com/deepmind/tapnet 😎Paper arxiv.org/pdf/2211.03726.pdf

🛸Flying-Drones Additive Manufacturing🛸 👉A novel aerial additive manufacturing (Aerial-AM) system via Drones 😎Review https://bit.ly/3XoLZOu 😎Paper www.nature.com/articles/s41586-022-04988-4

🪄The new SOTA in Text-to-3D is out!🪄 👉#Nvidia unveils Magic3D: generative #AI to create #3D textured mesh from text prompts 😎Review https://bit.ly/3Vb6jAO 😎Project deepimagination.cc/Magic3D 😎Paper arxiv.org/pdf/2211.10440.pdf

🔥#StableDiffusion Dataset is out! 🔥 👉DIFFUSIONDB: first large-scale text-to-image dataset: 14 MILLION images with Stable Diffusion! 😎Review https://bit.ly/3V9CpNh 😎Project poloclub.github.io/diffusiondb 😎Paper arxiv.org/pdf/2210.14896.pdf 😎Repo github.com/poloclub/diffusiondb

💎 3DiM: Diffusion Model by Google 💎 👉3DiM: diffusion model for 3D novel view synthesis from as few as a single image 😎Review bit.ly/3UTJFgA 😎Project 3d-diffusion.github.io 😎Paper arxiv.org/pdf/2210.04628.pdf

🐠 FathomNet: #AI in the Oceans 🐠 👉Open-source image dataset for AI about oceans and its inhabitants 😎Review https://bit.ly/3GsW3jh 😎Project fathomnet.org/fathomnet/#/ 😎Paper www.nature.com/articles/s41598-022-19939-2

🔥 ROVIS: Robust Online VIS 🔥 👉ROVIS is a novel method for robust online VIS that exhibits impressive accuracy on long clips 😎Review https://bit.ly/3UMugyv 😎Project zitongzhan.github.io/rovis_page/ 😎Paper arxiv.org/pdf/2211.09108.pdf

♾ The Universal Image Segmentation ♾ 👉OneFormer is the universal framework that unifies: semantic, instance & panoptic 🤯 😎Review https://bit.ly/3g4OAfD 😎Project praeclarumjj3.github.io/oneformer 😎Paper arxiv.org/pdf/2211.06220.pdf 😎Code github.com/SHI-Labs/OneFormer

🎃 eDiff-I: Generative AI by #Nvidia 🎃 👉eDiff-I: generative AI for text-to-image with instant style transfer & "paint-with-words" 😎Review https://bit.ly/3UEESzk 😎Project deepimagination.cc/eDiffi 😎Paper arxiv.org/pdf/2211.01324.pdf

🧶Open-Source Neural Inpainting Suite🧶 👉Lama Cleaner: a free and open-source inpainting tool powered by SOTA #AI model 😎Review https://bit.ly/3Ex2aSq 😎Project github.com/Sanster/lama-cleaner

🏔️ InfiniteNature-Zero: ∞ Video 🏔️ 👉Open-source generative #AI for unbounded flythrough videos of natural scenes 😎Review https://bit.ly/3hJYELa 😎Paper arxiv.org/pdf/2207.11148.pdf 😎Project infinite-nature-zero.github.io 😎Code https://github.com/google-research/google-research/tree/master/infinite_nature_zero

🔫 Real-Time Auto Neural Mapping 🔫 👉Robot can densely annotate a scene via fully-autonomous experimental interactions 😎Review https://bit.ly/3GfwQbY 😎Paper arxiv.org/pdf/2210.17325.pdf 😎Project ihaughton.github.io/RobE

🍉 Unifying Flow, Stereo & Depth 🍉 👉A unified neural model for motion and #3D perception tasks 😎Review https://bit.ly/3AbdnFk 😎Paper arxiv.org/pdf/2211.05783.pdf 😎Project haofeixu.github.io/unimatch/ 😎Code github.com/autonomousvision/unimatch