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

Malasia2 240 Tecnologías y Aplicaciones7 726...

📈 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 17 154 suscriptores, ocupando la posición 7 726 en la categoría Tecnologías y Aplicaciones y el puesto 2 240 en la región Malasia.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 17 154 suscriptores.

Según los últimos datos del 21 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -166, y en las últimas 24 horas de -6, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 23.63%. 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 4 057 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 22 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.

17 154

Suscriptores

-624 horas

-277 días

-16630 días

4 057

Visitas de la publicación

~ 1 17724 horas

~ 1 35348 horas

23.63%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

beta

Archivo de publicaciones

17 154

🥎POKEFLEX: Soft Object Dataset🥎 👉PokeFlex from ETH is a dataset that includes 3D textured meshes, point clouds, RGB & depth maps of deformable objects. Pretrained models & dataset announced💙 👉Review https://t.ly/GXggP 👉Paper arxiv.org/pdf/2410.07688 👉Project https://lnkd.in/duv-jS7a 👉Repo

17 154

💡Diffusion Models Relighting💡 👉#Netflix unveils DifFRelight, a novel free-viewpoint facial relighting via diffusion model. Precise lighting control, high-fidelity relit facial images from flat-lit inputs. 👉Review https://t.ly/fliXU 👉Paper arxiv.org/pdf/2410.08188 👉Project www.eyelinestudios.com/research/diffrelight.html

17 154

🥦Gaussian Splatting VTON🥦 👉GS-VTON is a novel image-prompted 3D-VTON which, by leveraging 3DGS as the 3D representation, enables the transfer of pre-trained knowledge from 2D VTON models to 3D while improving cross-view consistency. Code announced💙 👉Review https://t.ly/sTPbW 👉Paper arxiv.org/pdf/2410.05259 👉Project yukangcao.github.io/GS-VTON/ 👉Repo github.com/yukangcao/GS-VTON

17 154

🐏 EFM3D: 3D Ego-Foundation 🐏 👉#META presents EFM3D, the first benchmark for 3D object detection and surface regression on HQ annotated egocentric data of Project Aria. Datasets & Code released💙 👉Review https://t.ly/cDJv6 👉Paper arxiv.org/pdf/2406.10224 👉Project www.projectaria.com/datasets/aeo/ 👉Repo github.com/facebookresearch/efm3d

17 154

🔥 "Deep Gen-AI" Full Course 🔥 👉A fresh course from Stanford about the probabilistic foundations and algorithms for deep generative models. A novel overview about the evolution of the genAI in #computervision, language and more... 👉Review https://t.ly/ylBxq 👉Course https://lnkd.in/dMKH9gNe 👉Lectures https://lnkd.in/d_uwDvT6

17 154

🛳️ EVER Ellipsoid Rendering 🛳️ 👉UCSD & Google present EVER, a novel method for real-time differentiable emission-only volume rendering. Unlike 3DGS it does not suffer from popping artifacts and view dependent density, achieving ∼30 FPS at 720p on #NVIDIA RTX4090. 👉Review https://t.ly/zAfGU 👉Paper arxiv.org/pdf/2410.01804 👉Project half-potato.gitlab.io/posts/ever/

17 154

🦴 One-Image Object Detection 🦴 👉Delft University (+Hensoldt Optronics) introduces OSSA, a novel unsupervised domain adaptation method for object detection that utilizes a single, unlabeled target image to approximate the target domain style. Code released💙 👉Review https://t.ly/-li2G 👉Paper arxiv.org/pdf/2410.00900 👉Code github.com/RobinGerster7/OSSA

17 154

🍇SPARK: Real-time Face Capture🍇 👉Technicolor Group unveils SPARK, a novel high-precision 3D face capture via collection of unconstrained videos of a subject as prior information. New SOTA able to handle unseen pose, expression and lighting. Impressive results. Code & Model announced💙 👉Review https://t.ly/rZOgp 👉Paper arxiv.org/pdf/2409.07984 👉Project kelianb.github.io/SPARK/ 👉Repo github.com/KelianB/SPARK/

17 154

👩‍🦰 SOTA Gaussian Haircut 👩‍🦰 👉ETH et. al unveils Gaussian Haircut, the new SOTA in hair reconstruction via dual representation (classic + 3D Gaussian). Code and Model announced💙 👉Review https://t.ly/aiOjq 👉Paper arxiv.org/pdf/2409.14778 👉Project https://lnkd.in/dFRm2ycb 👉Repo https://lnkd.in/d5NWNkb5

17 154

🌾 New SOTA Edge Detection 🌾 👉CUP (+ ESPOCH) unveils the new SOTA for Edge Detection (NBED); superior performance consistently across multiple benchmarks, even compared with huge computational cost and complex training models. Source Code released💙 👉Review https://t.ly/zUMcS 👉Paper arxiv.org/pdf/2409.14976 👉Code github.com/Li-yachuan/NBED

17 154

🩰 Dressed Humans in the wild 🩰 👉ETH (+ #Microsoft ) ReLoo: novel 3D-HQ reconstruction of humans dressed in loose garments from mono in-the-wild clips. No prior assumptions about the garments. Source Code announced, coming 💙 👉Review https://t.ly/evgmN 👉Paper arxiv.org/pdf/2409.15269 👉Project moygcc.github.io/ReLoo/ 👉Code github.com/eth-ait/ReLoo

17 154

🎢 Robo-quadruped Parkour🎢 👉LAAS-CNRS unveils a novel RL approach to perform agile skills that are reminiscent of parkour, such as walking, climbing high steps, leaping over gaps, and crawling under obstacles. Data and Code available💙 👉Review https://t.ly/-6VRm 👉Paper arxiv.org/pdf/2409.13678 👉Project gepetto.github.io/SoloParkour/ 👉Code github.com/Gepetto/SoloParkour

17 154

🌏 JoyHallo: Mandarin Digital Human 🌏 👉JD Health faced the challenges of audio-driven video generation in Mandarin, a task complicated by the language’s intricate lip movements and the scarcity of HQ datasets. Impressive results (-> audio ON). Code Models available💙 👉Review https://t.ly/5NGDh 👉Paper arxiv.org/pdf/2409.13268 👉Project jdh-algo.github.io/JoyHallo/ 👉Code github.com/jdh-algo/JoyHallo

17 154

🌏 JoyHallo: Mandarin Digital Human 🌏 👉JD Health faced the challenges of audio-driven video generation in Mandarin, a task complicated by the language’s intricate lip movements and the scarcity of HQ datasets. Impressive results (-> audio ON). Code Models available💙 👉Review 👉Paper arxiv.org/pdf/2409.13268 👉Project jdh-algo.github.io/JoyHallo/ 👉Code github.com/jdh-algo/JoyHallo

17 154

⚽ SoccerNet 2024 Results ⚽ 👉SoccerNet is the annual video understanding challenge for football. These challenges aim to advance research across multiple themes in football. The 2024 results are out! 👉Review https://t.ly/DUPgx 👉Paper arxiv.org/pdf/2409.10587 👉Repo github.com/SoccerNet 👉Project www.soccer-net.org/

17 154

🧸Motion Instruction Fine-Tuning🧸 👉MotIF is a novel method that fine-tunes pre-trained VLMs to equip the capability to distinguish nuanced robotic motions with different shapes and semantic groundings. A work by MIT, Stanford, and CMU. Source Code announced, coming💙 👉Review https://t.ly/iJ2UY 👉Paper https://arxiv.org/pdf/2409.10683 👉Project https://motif-1k.github.io/ 👉Code coming

17 154

🌭Hand-Object interaction Pretraining🌭 👉Berkeley unveils HOP, a novel approach to learn general robot manipulation priors from 3D hand-object interaction trajectories. 👉Review https://t.ly/FLqvJ 👉Paper https://arxiv.org/pdf/2409.08273 👉Project https://hgaurav2k.github.io/hop/

17 154

💄Interactive Drag-based Editing💄 👉CSE unveils InstantDrag: novel pipeline designed to enhance editing interactivity and speed, taking only an image and a drag instruction as input. Source Code announced, coming💙 👉Review https://t.ly/hy6SL 👉Paper arxiv.org/pdf/2409.08857 👉Project joonghyuk.com/instantdrag-web/ 👉Code github.com/alex4727/InstantDrag

17 154

🫒 Omni Urban Scene Reconstruction 🫒 👉OmniRe is novel holistic approach for efficiently reconstructing HD dynamic urban scenes from on-device logs. It's able to create the simulation of reconstructed scenarios with actors in real-time (~60 Hz). Code released💙 👉Review https://t.ly/SXVPa 👉Paper arxiv.org/pdf/2408.16760 👉Project ziyc.github.io/omnire/ 👉Code github.com/ziyc/drivestudio

17 154

🐺 Diffusion Game Engine 🐺 👉#Google unveils GameNGen: the first game engine powered entirely by a neural #AI that enables real-time interaction with a complex environment over long trajectories at HQ. No code announced but I love it 💙 👉Review https://t.ly/_WR5z 👉Paper https://lnkd.in/dZqgiqb9 👉Project https://lnkd.in/dJUd2Fr6