AI with Papers - Artificial Intelligence & Deep Learning
رفتن به کانال در 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
نمایش بیشتر📈 تحلیل کانال تلگرام AI with Papers - Artificial Intelligence & Deep Learning
کانال AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 17 262 مشترک است و جایگاه 7 491 را در دسته فناوری و برنامه‌ها و رتبه 2 128 را در منطقه ماليزيا دارد.
📊 شاخص‌های مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 17 262 مشترک جذب کرده است.
بر اساس آخرین داده‌ها در تاریخ 23 اکتبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 255 و در ۲۴ ساعت گذشته برابر 2 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 18.93% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 7.17% واکنش نسبت به کل مشترکان کسب می‌کند.
- دسترسی پست‌ها: هر پست به طور میانگین 3 267 بازدید دریافت می‌کند. در اولین روز معمولاً 1 237 بازدید جمع‌آوری می‌شود.
- واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 20 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند framework, object, dataset, tba, depth تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
“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”
به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 24 اکتبر, 2026)، کانال همواره به‌روز و دارای دسترسی بالاست. تحلیل‌ها نشان می‌دهد مخاطبان به‌طور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامه‌ها تبدیل کرده‌اند.
17 262
مشترکین
+224 ساعت
+67 روز
+25530 روز
آرشیو پست ها
👉 A proof I'm not a bot...
My (short) interview to one of the biggest Italian media: AI in 2016, HPC / Quantum and how I created my startup: https://www.linkedin.com/posts/visionarynet_ai-itw25-ai-activity-7381215486115643392-t7an
Thanks for the support (and of course a new paper coming in a few hours)
🎷🎷 Clink! Chop! Thud! 🎷🎷
👉Sounding Object Detection: while an environment may contain many objects, only a few are directly involved in producing sound during an interaction. This model detects the sounding object given a video of an object interaction. Code/Data announced💙
👉Review https://t.ly/VK_1h
👉Paper https://lnkd.in/depNjVXm
👉Project https://lnkd.in/dF63EZFG
👉Repo TBA
🔩Code-Centric Agentic Education🔩
👉Show Lab unveils Code2Video: agentic, code-centric framework that generates HQ educational videos from knowledge points. Unlike pixel-based text-to-video models, this approach leverages executable Manim code to ensure clarity, coherence & reproducibility. Repo under MIT💙
👉Review https://t.ly/Fv4LJ
👉Paper https://arxiv.org/pdf/2510.01174
👉Repo https://github.com/showlab/Code2Video/
👉Project https://showlab.github.io/Code2Video/
👩🦱Physical-Hair Diffusion👩🦱
👉CONTROLHAIR is novel hybrid framework that integrates a physics simulator with conditional video diffusion to enable controllable dynamic hair rendering. Repo announced💙
👉Review https://t.ly/78LHr
👉Paper https://lnkd.in/epm-A9Fq
👉Project https://lnkd.in/evsjz298
👉Repo TBA
👔 Universal Image Restoration 👔
👉LucidFlux by HKUSTGZ is the universal image restoration framework built on a large-scale diffusion transformer that delivers photorealistic restorations of real-world low-quality (LQ) images, outperforming SOTA diffusion-based models across diverse degradations. Repo under custom Non-Commercial License💙
👉Review https://t.ly/Z5cA3
👉Paper https://arxiv.org/pdf/2509.22414
👉Project https://w2genai-lab.github.io/LucidFlux/
👉Repo https://github.com/W2GenAI-Lab/LucidFlux
🤖 Real-time Interactive Long Video 🤖
👉LONGLIVE by #Nvidia is a frame-level autoregressive framework for real-time & interactive long video generation. LONGLIVE accepts sequential user prompts and generates corresponding videos in real time. Repo under non-commercial license💙
👉Review https://t.ly/jJkdY
👉Paper arxiv.org/pdf/2509.22622
👉Project nvlabs.github.io/LongLive/
👉Repo github.com/NVlabs/LongLive
🤗huggingface.co/Efficient-Large-Model/LongLive-1.3B
🔥SOTA Detection w/ DINOv3🔥
👉DEIMv2 is the evolution of DEIM framework while leveraging DINOv3. Various model sizes, from an ultra-light version up to S, M, L, & X for a wide range of scenarios. Across these variants, DEIMv2 achieves SOTA. Repo Apache2.0💙
👉Review https://t.ly/P7jEH
👉Paper arxiv.org/pdf/2509.20787
👉Repo github.com/Intellindust-AI-Lab/DEIMv2
👉Project intellindust-ai-lab.github.io/projects/DEIMv2
🤬Music vs. Face Recognition🤬
👉At their recent concerts, Massive Attack turned surveillance into art: crafting a haunting audiovisual show that exposes the dangers of facial recognition tech. Audiences were scanned with mock surveillance, confronting them with the intrusive power of #AI in real time
👉Review https://t.ly/VMrPC
👉News https://t.ly/aj1an
A few “leaks” for you from the #Nvidia presentation I’m right now. Impressive stuff.
Ps: sorry for the shitty pics ♥️
🌀 CLOPS: Vision-Driven Avatar 🌀
👉CLOPS is the first human avatar solely uses egocentric vision to perceive its surroundings and navigate. CLOPS is able to realistically move in a scene and use egocentric vision in order to find a goal by combining a data driven low level motion prior with a Q-Learning policy. A loop of visual perception & motion. Code announced💙
👉Review https://t.ly/RXp64
👉Paper https://arxiv.org/pdf/2509.19259
👉Project markos-diomataris.github.io/projects/clops/
👉Repo TBA
🏆 MOSEv2 Challenge 2025 Winner 🏆
👉A practical solution for complex segmentation based on the Segment Concept (SeC), a concept-driven segmentation framework that shifts from conventional feature matching to the progressive construction and utilization of high-level, object-centric representations. Repo under Apache 2.0💙
👉Review https://t.ly/2MjNm
👉Paper https://arxiv.org/pdf/2509.19183
👉Paper (SeC) https://arxiv.org/pdf/2507.15852
👉Project https://rookiexiong7.github.io/projects/SeC/
👉Repo https://github.com/OpenIXCLab/SeC
🫓 WINNER of LSVOS Challenge 🫓
👉SaSaSa2VA introduces Segmentation Augmentation to improve global video understanding while remaining efficient, and employs Selective Averaging at inference to robustly fuse complementary predictions. This approach achieves SOTA on the 7th LSVOS Challenge (RVOS track). A practical solution with full repo under Apache💙
👉Review https://t.ly/aH4mB
👉Paper https://arxiv.org/pdf/2509.16972
👉Repo https://github.com/magic-research/Sa2VA
🐳 Invariant Saliency Detection 🐳
👉SI-SOD: invariant salient object detection is a paper investigating a fundamental yet underexplored issue in Salient Object Detection (SOD): the size-invariant property for evaluation protocols, particularly in scenarios when multiple salient objects of significantly different sizes appear within a single image. Repo released💙
👉Review https://lnkd.in/p/dZBfbSsf
👉Paper https://arxiv.org/pdf/2509.15573
👉Project https://ferry-li.github.io/SI_SOD/
👉Repo https://github.com/Ferry-Li/SI-SOD
🔥🔥 It's time to decide whether you want to give LinkedIn your data for AI training or not 🔥🔥
Set here: http://linkedin.com/mypreferences/d/settings/data-for-ai-improvement
