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
🌻 Extending Mona Lisa with AI 🌻
👉 A guy on Reddit extends Mona Lisa Painting with #Photoshop AI. The result is surprising.
😎More https://t.ly/j_2r
🦜 ColorDiffuser: Text-to-Video Colorization 🦜
👉HK University unveils ColorDiffuser: adapting pre-trained text-to-image latent diffusion model for video colorization
😎Report https://t.ly/XGv_
😎Paper arxiv.org/pdf/2306.01732.pdf
😎Project colordiffuser.github.io/
😎Code github.com/ColorDiffuser/ColorDiffuser
🗽 Neuralangelo Digital Twins. INSANE🗽
👉 A novel framework from #Nvidia for Hi-Fi 3D Digital twins.
😎Report https://t.ly/XGv_
😎Paper research.nvidia.com/labs/dir/neuralangelo/paper.pdf
😎Project research.nvidia.com/labs/dir/neuralangelo
🎗️ 4D Humans with Transformers 🎗️
👉Novel approach to reconstruct and track humans (even in unusual poses)
😎Report https://t.ly/XGv_
😎Paper arxiv.org/pdf/2305.20091.pdf
😎Project shubham-goel.github.io/4dhumans/#
😎Code github.com/shubham-goel/4D-Humans
🦁 Open Semantic Segmentation 🦁
👉SSSegmentation: open source supervised semantic segmentation toolbox based on #PyTorch
😎Review https://t.ly/ZE9q
😎Paper arxiv.org/pdf/2305.17091.pdf
😎Code github.com/SegmentationBLWX/sssegmentation
🌊 Neural Dynamic Image-Based Rendering 🌊
👉 DynIBaR: synthesizing novel views from monocular video depicting a complex dynamic scene.
😎Review https://t.ly/90Kw
😎Paper arxiv.org/pdf/2211.11082.pdf
😎Project https://dynibar.github.io/
😎Code github.com/google/dynibar
🍶 AVOS via Multiscale Encoder-Decoder ViT 🍶
👉 MED-VT, world's first Multiscale Encoder Decoder Video Transformer for AVOS
😎Review https://bit.ly/3MohFi1
😎Paper arxiv.org/pdf/2304.05930.pdf
😎Project rkyuca.github.io/medvt
😎Code github.com/rkyuca/medvt
🗺️ AI-generated stereotypical men in [Country] 🗺️
👉A thread about generating stereotypical person from 15 countries all around the world. And yes, Italian love Pizza.
😎 More https://bit.ly/3oo0t4c
🀄 Drag-GAN: user-friendly image-manipulation 🀄
👉 Manual deforming of (real and generated) images over pose, shape, expression and layout.
😎Review https://bit.ly/3BFyXlR
😎Paper arxiv.org/pdf/2305.10973.pdf
😎Project vcai.mpi-inf.mpg.de/projects/DragGAN
😎Code github.com/XingangPan/DragGAN
🎫 100% Mask-Free VIS 🎫
👉ETH Z unveils MaskFreeVIS: novel high-performing VIS without any mask annotations.
😎Review https://bit.ly/3Wg7CQB
😎Paper arxiv.org/pdf/2303.15904.pdf
😎Project www.vis.xyz/pub/maskfreevis/
😎Code github.com/SysCV/maskfreevis
👚 Multi-Layered 3D Garments Animation 👚
👉S-Lab unveils LayersNet: animating multi-layered garments driven by various external forces, such as human bodies & wind
😎Review https://bit.ly/435b42F
😎Paper arxiv.org/pdf/2305.10418.pdf
😎Project mmlab-ntu.github.io/project/layersnet
🪰 #3D Auto-Reconstruction 🪰
👉AutoRecon: automated discovery & reconstruction of objects from multi-view pics.
😎Review https://bit.ly/3MxI0f4
😎Paper arxiv.org/pdf/2305.08810.pdf
😎Project zju3dv.github.io/autorecon/
😎Code github.com/zju3dv/AutoRecon
🍿 De-Aging Harrison Ford via SD 🍿
👉Stable Diffusion Deepfake for Hollywood: a preview of the next autotune of the entertainment industry. A Reddit discussion👇
😎 More: https://bit.ly/41EzaQK
🛸 Virtual Occlusions in #AR 🛸
👉Niantic (#pokemongo) on a novel approach for virtual assets to appear ‘sitting among’ the real world objects
😎Review https://bit.ly/3o04wn6
😎Paper arxiv.org/pdf/2305.07014.pdf
😎Project nianticlabs.github.io/implicit-depth
😎Code github.com/nianticlabs/implicit-depth
🦕 HACMan: 6D Non-Prehensile Manipulation 🦕
👉#META (+CMU) unveils HACMan, novel 6D non-prehensile manipulation of objects
😎Review https://bit.ly/3NP1jl1
😎Paper arxiv.org/pdf/2305.03942.pdf
😎Project hacman-2023.github.io
🐊 RelPose++: SOTA 6D from 2-8 pics 🐊
👉CMU unveils a novel neural method for 6D camera poses from only 2-8 images
😎Review https://bit.ly/42ioJ6K
😎Paper arxiv.org/pdf/2305.04926.pdf
😎Project amyxlase.github.io/relpose-plus-plus
😎Code github.com/amyxlase/relpose-plus-plus
🦒 Look mom, I'm a giraffe 🦒
👉 A patent to transpose adversarial patches onto a knitted fabric. Be undetectable or associated with incorrect category such as "animal" (giraffe, zebra, etc)
😎 More: https://www.linkedin.com/posts/visionarynet_artificialintelligence-machinelearning-ml-activity-7059835420628369408-lJOs
🌱 Segment Everything Everywhere 🌱
👉 Segmenting everything using visual/language prompts (BBs, scribbles, text & audio)
😎Review https://bit.ly/3LEiOmx
😎Paper arxiv.org/pdf/2304.06718.pdf
😎Demo huggingface.co/spaces/xdecoder/SEEM
😎Code github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once
🔥 Track Anything: SAM-powered tracking 🔥
👉 SUSTech VIP Lab proposes TAM, a "novel" video tracker powered by SAM
😎Review https://bit.ly/44jwI4W
😎Paper arxiv.org/pdf/2304.11968.pdf
😎Code github.com/gaomingqi/Track-Anything
Hi Everybody,
right now I'm flying to NY for a business trip!
👉 Is there anyone is studying/working @NYU? I'd be super excited to see the campus and (eventually) attend to a few lessons about AI/CV/MATH on Monday (or this Friday)
Send me a DM -> @argovision
