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 17 264 مشتركاً، محتلاً المرتبة 7 532 في فئة التكنولوجيات والتطبيقات والمرتبة 2 128 في منطقة ماليزيا.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 17 264 مشتركاً.
بحسب آخر البيانات بتاريخ 30 أكتوبر, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 223، وفي آخر 24 ساعة بمقدار 3، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 16.65%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 7.01% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 2 874 مشاهدة. وخلال اليوم الأول يجمع عادةً 1 211 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 31 أكتوبر, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
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أرشيف المشاركات
🔥🔥 UPDATE 🔥🔥
Code Released: https://github.com/apple/ml-mobileone
🧱 Assembling #LEGO with #AI 🧱
👉Step-by-step assembly manual created by human into machine-interpretable instructions
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Stanford + MIT + #Google 🤯
✅MEPNet: Manual-to-Executable-Plan Net
✅Manual to machine-executable plan
✅2D manual - 3D geometric shape
✅Reasoning on 3D alignments of legos
More: https://bit.ly/3PCwn5C
💄DEVIANT: SOTA in mono-3D detection💄
👉A novel Depth EquiVarIAnt NeTwork for 3D monocular detection in the wild
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Michigan + #Meta + Ford 🤯
✅Depth-equi. + scale equiv. steerable
✅New SOTA on KITTI & Waymo
✅Ok cross-dataset -> generalization
More: https://bit.ly/3OEFtgK
👹Multiface Neural Rendering 👹
👉A new multi-view, Hi-Res data collected at #META Reality Labs for neural face
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Mugsy, large scale multi-cam apparatus
✅High-Res sync facial performance
✅Closing the gap in accessing HQ data
✅Suitable for #VR & #mixedreality
More: https://bit.ly/3b6XfeL
🎷🎷OMNI3D: #3D Objects in the Wild🎷🎷
👉#3D detection: 234k images, 3M+ instances & 97 categories
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅OMNI3D from publicly released dataset
✅234k pics, 3M+ annotation with 3D box
✅97 categories such as sofa, table, cars
✅Fast (450x) and exact algorithm for IoU
✅Cube R-CNN: novel 3D object detector
More: https://bit.ly/3cznjzG
🔥 #AIwithPapers: we are 3,500+! 🔥
💙💛 Ready for YOLO 10, 11, π, ∞, Ψ, and more? The more we are, the faster we catch'em all 💙💛
😈 Invite your friends -> https://t.me/AI_DeepLearning
🪰NUWA-Infinity is out!🪰
👉∞ generation by #Microsoft: arbitrarily-sized HD images and long videos 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Unconditional Image Gen.
✅Text-to-Image/Text-to-Clip
✅Animation / Out-painting
✅Hi-res, arbitrary long clip
✅NCP for patches caching
More: https://bit.ly/3zmBf9f
🦚 TimeLens++: Event-based Interpolation 🦚
👉Novel event-based interpolation with non-linear flow & multi-scale fusion
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel motion spline estimator
✅Non-linear continuous event/frames flow
✅Multi-feature fusion, gated compression
✅Novel hybrid dataset with 100+ videos
More: https://bit.ly/3yJyY6g
🔥Important update from #OpenAI🔥
👉 https://openai.com/blog/reducing-bias-and-improving-safety-in-dall-e-2/
💣 HD Neural Avatar @130FPS 💣
👉Samsung unveils MegaPortraits: novel one-shot creation of HD neural human avatar
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅One-shot neural avatars, SOTA up 512p
✅"Upgrading" to megapixel via more pics
✅First Neural Head Avatars in HD
✅Up to to 130 FPS via #GPU
More: https://bit.ly/3oboWWT
🔥OmniBenchmark: CV beyond ImageNet🔥
👉 21 realms, 7,000+ concepts and 1M+ images. Far beyond ImageNet!
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅vs. ImageNet: 2.5x realms, 9x concepts
✅Conciseness: no concept overlapping
✅ReCo: Relational Contrastive Learning
✅New supervised contrastive learning SOTA
More: https://bit.ly/3RJRKU0
🔥Grand Unification of Object Tracking🔥
👉UNICORN: unified method for SOT, MOT, VOS, & MOTS with a single neural net. 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Great unification for 4 tracking tasks
✅Bridging methods / pixel-wise corresp.
✅SOTA on 8 challenging benchmarks
✅Source code under MIT License
More: https://bit.ly/3o74h6g
🔥🔥 Update 🔥🔥
👉Code https://github.com/THUDM/CogVideo
👉Demo https://wudao.aminer.cn/cogvideo/
More: https://bit.ly/3yP86BQ
🍰 Long-Term Object Segmentation 🍰
👉XMem: object segmentation for long clips with unified feature memory stores
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Inspired by Atkinson–Shiffrin model
✅Stores with different temporal scales
✅Memory consolidation algorithm
✅Compact/powerful long-term memory
✅Source code and models available
More: https://bit.ly/3PP0EOn
☀️ 4D Neural Relightable Humans ☀️
👉Relighting4D: free-viewpoints relighting of humans under unknown illuminations
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Relight dynamic, free viewpoints
✅Disentangled reflectance/geometry
✅SOTA on synthetic/real datasets
✅Code/models under MIT License
More: https://bit.ly/3RF3yH9
🤹♂️ K-Means Mask Transformer 🤹♂️
👉#Google AI unveils kMaX-DeepLab, novel E2E method for segmentation
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅kMaX-DeepLab: k-means Mask Xformer
✅Rethinking relationship pixels / object
✅Cross-attention -> k-means clustering
✅The new SOTA on several dataset
More: https://bit.ly/3O2QV5I
👽 Neural I2I with a few shoots 👽
👉#Alibaba unveils a novel portrait stylization. Limited samples (∼100) -> HD outputs
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Calibration first, translation later
✅Balanced distribution to calibrate bias
✅Spatially semantic constraints via geometry
✅Source code and models soon available!
More: https://bit.ly/3IwOmHO
📟📟AI-Designed Circuits with Deep RL📟📟
👉#Nvidia unveils an #AI to design circuits from scratch, smaller and faster than SOTA ones
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Parallel prefix circuits for Hi-Perf
✅RL framework to explore the circuit space
✅Smaller, Faster, Power-- from the scratch
More: https://bit.ly/3yY9dk7
🦒 Text2LIVE: Text-Driven Neural Editing 🦒
👉#Amazon unveils a novel #AI for text-driven edit of videos. Insane! 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Semantic edits of real-world videos
✅Edit layer–RGBA representing target
✅Edit layers synthesized on single input
✅No masks or a pre-trained generator
More: https://bit.ly/3NVP6aE
😊😎 Seq-DeepFake via Transformers 😎😊
👉S-Lab opens Seq-DeepFake: Detecting Sequential DeepFake Manipulation
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Seq-DeepFake: sequences of facial edits
✅Dataset: 85k #deepfake manipulation
✅Powerful Seq-DeepFake Transformer
✅Code, dataset and models available!
More: https://bit.ly/3ACQXhi
