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
إظهار المزيد📈 نظرة تحليلية على قناة تيليجرام AI with Papers - Artificial Intelligence & Deep Learning
تُعد قناة AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 17 261 مشتركاً، محتلاً المرتبة 7 543 في فئة التكنولوجيات والتطبيقات والمرتبة 2 144 في منطقة ماليزيا.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 17 261 مشتركاً.
بحسب آخر البيانات بتاريخ 26 أكتوبر, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 250، وفي آخر 24 ساعة بمقدار 1، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 17.43%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 7.04% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 3 008 مشاهدة. وخلال اليوم الأول يجمع عادةً 1 216 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 16.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل framework, object, dataset, tba, depth.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“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”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 27 أكتوبر, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
17 261
المشتركون
+124 ساعات
+97 أيام
+25030 أيام
أرشيف المشاركات
🌻 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
