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
Mostrar más📈 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 17 261 suscriptores, ocupando la posición 7 543 en la categoría Tecnologías y Aplicaciones y el puesto 2 144 en la región Malasia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 17 261 suscriptores.
Según los últimos datos del 26 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 250, y en las últimas 24 horas de 1, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 17.43%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 7.04% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 3 008 visualizaciones. En el primer día suele acumular 1 216 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 16.
- 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 27 octubre, 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.
17 261
Suscriptores
+124 horas
+97 días
+25030 días
Archivo de publicaciones
🪅Inpaint Anything: Segmentation + Inpainting 🪅
👉Remove / Fill /Replace anything (also via prompt). "Inpainting Anything", a new paradigm of “clicking & filling"
😎Review https://bit.ly/43JNREE
😎Paper arxiv.org/pdf/2304.06790.pdf
😎Code github.com/geekyutao/Inpaint-Anything
🌻 DDS: diffusive text-based image editing 🌻
👉Google unveils a novel text-based image editing for modifications of an input image towards a text description.
😎Review https://bit.ly/3L52UBl
😎Paper arxiv.org/pdf/2304.07090.pdf
😎Project delta-denoising-score.github.io
🪬 META's Animated Drawings is out! 🪬
👉#META unveils an easy-to-use method for animating human-like figures drawn by children.
😎Review https://bit.ly/3mGeQQv
😎Paper arxiv.org/pdf/2303.12741.pdf
😎Project fairanimateddrawings.com/site/home
😎Dataset (coming) https://fairanimateddrawings.com/site/dataset
😎Code https://github.com/facebookresearch/AnimatedDrawings#amateur-drawings-dataset
🔥 ALERT: Stable Diffusion XL just launched! 🔥
👉SDXL the new generative AI by Stability.AI for images from text. Up to 1024x1024 resolution, for free.
😎More https://bit.ly/41wrh0j
🥦 Zip-NeRF: the Anti-Aliasing NeRF 🥦
👉#Google unveils a novel version of NeRF able to fix the aliasing problem being 22x faster in training than SOTA.
😎Review https://bit.ly/3L1hZ6M
😎Paper arxiv.org/pdf/2304.06706.pdf
😎Project https://jonbarron.info/zipnerf
👗DreamPose: Fashion I-2-V Diffusion👗
👉 Turning fashion photos into realistic videos via driving pose sequence
😎Review https://bit.ly/3AdNtAN
😎Paper arxiv.org/pdf/2304.06025.pdf
😎Code github.com/johannakarras/DreamPose
😎Project grail.cs.washington.edu/projects/dreampose
💦SegGPT: Segmenting Everything (In Context)💦
👉BAAI unveils SegGPT, a generalist model for segmenting everything in context
😎Review https://bit.ly/3zFkUf2
😎Paper arxiv.org/pdf/2304.03284.pdf
😎Code github.com/baaivision/Painter
😎Demo huggingface.co/spaces/BAAI/SegGPT
🔥 "Segmenting Anything". CRAZY! 🔥
👉#Google unveils a novel model and (1B+) dataset for neural segmentation 🤯
😎Review https://bit.ly/3ZFhjrX
😎Paper https://bit.ly/43788DC
😎Project https://segment-anything.com
😎Code github.com/facebookresearch/segment-anything
🔥 "Segmenting Anything". CRAZY! 🔥
👉#Google unveils a novel model and (1B+) dataset for neural segmentation 🤯
😎Paper https://bit.ly/43788DC
😎Project https://segment-anything.com/
😎Code github.com/facebookresearch/segment-anything
🦒SOTA ALERT: Synthetic 3D Cities 🦒
👉UrbanGIRAFFE: novel SOTA generator of photorealistic #3D-aware urban image with full controllability
😎Review https://bit.ly/42ZdX5Q
😎Paper arxiv.org/pdf/2303.14167.pdf
😎Project lv3d.github.io/urbanGIRAFFE
🛎 Neural 6-DoF Tracking + 3D Reconstruction 🛎
👉The novel SOTA for real-time 6-DoF tracking of unknown objects, while simultaneously performing neural 3D
😎Review https://bit.ly/3lHVoT2
😎Paper arxiv.org/pdf/2303.14158.pdf
😎Project bundlesdf.github.io/
📊 Neural vs. Old School ML 📊
✅ The choice of Deep Learning-based AI vs. traditional ML may depend on the specific application and problem being addressed.
👉 What's your favorite approach? Please vote: https://bit.ly/3LQU774
📊 Neural vs. Old School ML 📊
✅ The choice of Deep Learning-based AI vs. traditional ml may depend on the specific application and problem being addressed.
👉 What's your favorite approach? Please vote: https://bit.ly/3LQU774
🥦 ReBotNet: Neural Real-Time Enhancement 🥦
👉#Google unveils ReBotNet, novel real-time video enhancement for live video calls & streams
😎Review https://bit.ly/3z8oqhG
😎Paper arxiv.org/pdf/2303.13504.pdf
😎Project jeya-maria-jose.github.io/rebotnet-web
🪲Neural 4K Color Style Transfer🪲
👉#Adobe 4K color style transfer: no artifacts, low memory & super-speed!
😎Review https://bit.ly/3TNKtUE
😎Paper arxiv.org/pdf/2303.13511.pdf
😎Project zhkkke.github.io/NeuralPreset
😎Code github.com/ZHKKKe/NeuralPreset
😎Demo zhkkke.github.io/NeuralPreset/#/editor
🔥 Is ChatGPT (close to) an AGI? 🔥
👉According to Microsoft #ChatGPT is an early (yet still incomplete) version of an artificial general intelligence system. Math, coding, vision, medicine, law, psychology and more.
👉Flame here: https://bit.ly/3K3Q1XC 🤣
🌈 #3D Editing with Instructions 🌈
👉A novel method for editing NeRF scenes with text-instructions
😎Review https://bit.ly/3K3putM
😎Paper https://arxiv.org/pdf/2303.12789.pdf
😎Project https://instruct-nerf2nerf.github.io
🛌 CC3D: Layout-Conditioned 3D Generation 🛌
👉A novel step towards the realistic multi-object scene generation
😎Review https://bit.ly/3JXG0v3
😎Paper arxiv.org/pdf/2303.12074.pdf
😎Project sherwinbahmani.github.io/cc3d
😎Code github.com/sherwinbahmani/cc3d
📘 Free Book: Understanding Deep Learning 📘
👉From MIT Press, a fresh book for mastering the Deep Learning & #AI
😎Download https://bit.ly/3JUHMNv
💀 SDFStudio: Unified Surface Reconstruction 💀
👉A unified (and open) framework for neural implicit surface reconstruction
😎Review https://bit.ly/3yUvuP2
😎Project autonomousvision.github.io/sdfstudio
😎Code github.com/autonomousvision/sdfstudio
😎Doc github.com/autonomousvision/sdfstudio/blob/master/docs/sdfstudio-methods.md
