¡Ya disponible! Investigación de Telegram 2025 — los principales insights del año 
AI with Papers - Artificial Intelligence & Deep Learning
Ir al canal en Telegram
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 17 147 suscriptores, ocupando la posición 7 723 en la categoría Tecnologías y Aplicaciones y el puesto 2 241 en la región Malasia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 17 147 suscriptores.
Según los últimos datos del 23 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -190, y en las últimas 24 horas de -2, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 25.09%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 6.86% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 4 302 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 24 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.
17 147
Suscriptores
-224 horas
-367 días
-19030 días
Archivo de publicaciones
🪐 Spacecraft Pose Estimation 🪐
👉SnT (Luxembourg) unveils the most advanced event-based dataset for Spacecrafts: Unreal Engine + data from ICNS simulator + Real images + Real event data acquired in lab
😎Review https://t.ly/m8JPB
😎Paper https://lnkd.in/d_edvc3n
😎Project https://lnkd.in/dPp375aY
🫀 Neural Segmentation of Human 🫀
👉TotalSegmentator_v2: segmenting 104 anatomical structures (27 organs, 59 bones, 10 muscles, 8 vessels) in CT. Now suitable in 3D Slicer, open source platform for image visualization.
😎Review https://t.ly/yHMm1
😎Code https://lnkd.in/dvgrbsCE
😎Paper https://lnkd.in/dkwHuuzU
🔥 Hu.ma.ne #AI Pin is out! 🔥
👉Hu.ma.ne just launched #AI Pin: the new standalone AI-powered screenless device. Running on the GPT-4 LLMs, suitable for real-time translation. #AI-powered camera and laser projector
😎 More https://t.ly/CXz95
🐪 30x Faster Neural Large Scenes 🐪
👉 NeuRas: realistic real-time novel-view synthesis of VERY large scenes (>10000 m2 ). 30× faster rendering than previous SOTA w/ comparable or better realism
😎Review https://t.ly/ELJSE
😎Paper https://arxiv.org/pdf/2311.05607.pdf
😎Project https://waabi.ai/NeuRas/
🛋️ 3DiffTection: new SOTA 3D detection 🛋️
👉#Nvidia unveils 3DiffTection, the new SOTA for 3D object detection from single images. A powerful 3D detector powered by diffusion model
😎Review https://t.ly/PciXY
😎Project research.nvidia.com/labs/toronto-ai/3difftection
😎Paper https://arxiv.org/pdf/2311.04391.pdf
😎Code https://github.com/nv-tlabs/3DiffTection
🥻Sewformer: Towards Virtual Cloth🥻
👉SEA AI Lab unveils a novel #AI to recovery the garment sewing patterns from daily photos for #AR / #VR worlds
😎Review https://t.ly/MwpAV
😎Project https://sewformer.github.io/
😎Paper https://arxiv.org/pdf/2311.04218.pdf
😎Code https://github.com/sail-sg/sewformer
🔥 Does GPT-4 Pass the Turing Test? 🔥
👉No. I mean...not yet. Read this Paper from UC San Diego👇
😎Review https://t.ly/o8HgM
😎 Paper https://arxiv.org/pdf/2310.20216.pdf
🚛 OYSTER: unsupervised detection w/ LIDAR 🚛
👉Waabi unveils OYSTER: a novel unsupervised object detection from LiDAR point clouds.
😎Review https://t.ly/EMi58
😎Project https://waabi.ai/oyster/
😎Paper arxiv.org/pdf/2311.02007.pdf
👣 Foot via Synthetic Data 👣
👉 50,000 synthetic/photorealistic foot images + a novel SOTA library for foot
😎Review https://t.ly/TVanP
😎Paper https://arxiv.org/pdf/2310.18279.pdf
😎Project https://ollieboyne.github.io/FOUND
😎Code https://github.com/OllieBoyne/FOUND
🍄 Video Understanding with GPT-4V(ision) 🍄
👉 #Microsoft unveils MM-Vid, the most advanced video understanding framework (w/ #chatgpt4). Impressive results on long-form videos and intricate tasks such as audio description & multimodal high-level comprehension
😎Review https://t.ly/RISMm
😎Paper arxiv.org/pdf/2310.19773.pdf
😎Project https://multimodal-vid.github.io
✌️ Relighted 3D Interacting Hands 🤞
👉#META unveils Re:InterHand: a large dataset of relighted 3D interacting hands
😎Review https://t.ly/I1dQk
😎Paper arxiv.org/pdf/2310.17768.pdf
😎Project mks0601.github.io/ReInterHand
😎Data github.com/mks0601/ReInterHand
🧂 SOTA RGB-D Video Salient Object 🧂
👉 DCTNet+ (model) and RDVS(dataset) for a new SOTA in Video Saliency Object Detection
😎Review https://t.ly/DapLV
😎Code github.com/kerenfu/RDVS
😎Paper arxiv.org/pdf/2310.15482.pdf
🥤NanoSAM: SAM on low-cost boards🥤
👉NanoSAM is a Segment Anything variant capable of running in real-time on #NVIDIA Jetson Orin with TensorRT
😎Review https://t.ly/UErq_
😎Tutorial https://github.com/NVIDIA-AI-IOT/nanosam
🪛 PACE: in-the-wild SOTA Motion 🪛
👉#Nvidia unveils the novel SOTA to estimate the human motion in a global scene from moving cams. Stunning results.
😎Review https://t.ly/20you
😎Project https://nvlabs.github.io/PACE
😎Paper https://arxiv.org/pdf/2310.13768.pdf
🧡 Rotoscoping Prince Of Persia (1985) 🧡
👉 A rare footage for the animation of Prince of Persia (1989). Damn Romantic.
😎 More https://t.ly/xJife
🍈 Cutie: VOS with heavy occlusions🍈
👉Cutie: novel VOS for challenging scenarios with heavy occlusions & distractors
😎Review https://t.ly/W3FR-
😎Paper arxiv.org/pdf/2310.12982.pdf
😎Project https://hkchengrex.com/Cutie
😎Code https://github.com/hkchengrex/Cutie
🛣️ Holistic Parking Detection (YOLO) 🛣️
👉 One-step Holistic Parking Slot Network: a tailor-made adaptation of YOLOv4 algorithm for all-shaped parking slot detection
😎Review https://t.ly/2l4ZG
😎Paper arxiv.org/pdf/2310.11629.pdf
🍡4K4D: Real-Time 4D View at 4K🍡
👉THE new SOTA in view synthesis of dynamic 3D scenes at 4K resolution is out. 30x faster, up to 400 FPS. Nuts!
😎Review https://t.ly/6ddQh
😎Paper arxiv.org/pdf/2310.11448.pdf
😎Project zju3dv.github.io/4k4d/
😎Code github.com/zju3dv/4K4D
😻 CatFLW: Cat Neural Landmarks 😻
👉Landmark convolution neural network-based model for cat faces
😎Review https://t.ly/Y3mQ8
😎Paper arxiv.org/pdf/2305.04232.pdf
😎Dataset www.tech4animals.org/catflw
🌱 Pose-Format: All-in-One Pose 🌱
👉 Pose-format: a comprehensive toolkit designed for human pose: unified, flexible, and easy-to-use
😎Review https://t.ly/rFrhq
😎Paper arxiv.org/pdf/2310.09066.pdf
😎Code github.com/sign-language-processing/pose
