uz
Feedback
AI with Papers - Artificial Intelligence & Deep Learning

AI with Papers - Artificial Intelligence & Deep Learning

Kanalga Telegram’da o‘tish

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

Ko'proq ko'rsatish

📈 Telegram kanali AI with Papers - Artificial Intelligence & Deep Learning analitikasi

AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 17 058 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 639-o'rinni va Malayziya mintaqasida 2 196-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 17 058 obunachiga ega bo‘ldi.

12 Iyul, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -149 ga, so‘nggi 24 soatda esa 9 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 17.34% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 7.54% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 2 958 marta ko‘riladi; birinchi sutkada odatda 1 287 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 15 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent framework, object, dataset, tba, depth kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
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

Yuqori yangilanish chastotasi (oxirgi ma’lumot 13 Iyul, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

17 058
Obunachilar
+924 soatlar
-357 kunlar
-14930 kunlar
Postlar arxiv
👣 Foot via Synthetic Data 👣 👉 50,000 synthetic/photorealistic foot images + a novel SOTA library for foot 😎Review https://t.ly/TVanP 😎Paper https://arxiv.org/pdf/2310.18279.pdf 😎Project https://ollieboyne.github.io/FOUND 😎Code https://github.com/OllieBoyne/FOUND

🍄 Video Understanding with GPT-4V(ision) 🍄 👉 #Microsoft unveils MM-Vid, the most advanced video understanding framework (w/ #chatgpt4). Impressive results on long-form videos and intricate tasks such as audio description & multimodal high-level comprehension 😎Review https://t.ly/RISMm 😎Paper arxiv.org/pdf/2310.19773.pdf 😎Project https://multimodal-vid.github.io

✌️ Relighted 3D Interacting Hands 🤞 👉#META unveils Re:InterHand: a large dataset of relighted 3D interacting hands 😎Review https://t.ly/I1dQk 😎Paper arxiv.org/pdf/2310.17768.pdf 😎Project mks0601.github.io/ReInterHand 😎Data github.com/mks0601/ReInterHand

🧂 SOTA RGB-D Video Salient Object 🧂 👉 DCTNet+ (model) and RDVS(dataset) for a new SOTA in Video Saliency Object Detection 😎Review https://t.ly/DapLV 😎Code github.com/kerenfu/RDVS 😎Paper arxiv.org/pdf/2310.15482.pdf

🥤NanoSAM: SAM on low-cost boards🥤 👉NanoSAM is a Segment Anything variant capable of running in real-time on #NVIDIA Jetson Orin with TensorRT 😎Review https://t.ly/UErq_ 😎Tutorial https://github.com/NVIDIA-AI-IOT/nanosam

🪛 PACE: in-the-wild SOTA Motion 🪛 👉#Nvidia unveils the novel SOTA to estimate the human motion in a global scene from moving cams. Stunning results. 😎Review https://t.ly/20you 😎Project https://nvlabs.github.io/PACE 😎Paper https://arxiv.org/pdf/2310.13768.pdf

🧡 Rotoscoping Prince Of Persia (1985) 🧡 👉 A rare footage for the animation of Prince of Persia (1989). Damn Romantic. 😎 More https://t.ly/xJife

🍈 Cutie: VOS with heavy occlusions🍈 👉Cutie: novel VOS for challenging scenarios with heavy occlusions & distractors 😎Review https://t.ly/W3FR- 😎Paper arxiv.org/pdf/2310.12982.pdf 😎Project https://hkchengrex.com/Cutie 😎Code https://github.com/hkchengrex/Cutie

🛣️ Holistic Parking Detection (YOLO) 🛣️ 👉 One-step Holistic Parking Slot Network: a tailor-made adaptation of YOLOv4 algorithm for all-shaped parking slot detection 😎Review https://t.ly/2l4ZG 😎Paper arxiv.org/pdf/2310.11629.pdf

🍡4K4D: Real-Time 4D View at 4K🍡 👉THE new SOTA in view synthesis of dynamic 3D scenes at 4K resolution is out. 30x faster, up to 400 FPS. Nuts! 😎Review https://t.ly/6ddQh 😎Paper arxiv.org/pdf/2310.11448.pdf 😎Project zju3dv.github.io/4k4d/ 😎Code github.com/zju3dv/4K4D

😻 CatFLW: Cat Neural Landmarks 😻 👉Landmark convolution neural network-based model for cat faces 😎Review https://t.ly/Y3mQ
😻 CatFLW: Cat Neural Landmarks 😻 👉Landmark convolution neural network-based model for cat faces 😎Review https://t.ly/Y3mQ8 😎Paper arxiv.org/pdf/2305.04232.pdf 😎Dataset www.tech4animals.org/catflw

🌱 Pose-Format: All-in-One Pose 🌱 👉 Pose-format: a comprehensive toolkit designed for human pose: unified, flexible, and easy-to-use 😎Review https://t.ly/rFrhq 😎Paper arxiv.org/pdf/2310.09066.pdf 😎Code github.com/sign-language-processing/pose

👗👗 AG3D: SOTA #3D clothed avatars from 2D👗👗 👉The novel SOTA in adversarial generative model of realistic 3D people is out. 😎Review https://t.ly/vnJO7 😎Paper zj-dong.github.io/AG3D/assets/paper.pdf 😎Project https://zj-dong.github.io/AG3D 😎Code https://github.com/zj-dong/AG3D

🦹‍♀️ Snap's Hyper-Realistic Human 🦹‍♀️ 👉New diffusive #AI by Snap that generates in-the-wild human images with hyper-reali
🦹‍♀️ Snap's Hyper-Realistic Human 🦹‍♀️ 👉New diffusive #AI by Snap that generates in-the-wild human images with hyper-realism. Swipe the gallery, NUTS!👇 😎Gallery https://t.ly/cG74X 😎Paper arxiv.org/pdf/2310.08579.pdf 😎Project snap-research.github.io/HyperHuman 😎Code github.com/snap-research/HyperHuman

🙋 Full Human Motion 🙋 👉OmniControl by Google is novel framework for text-conditioned human motion generation model based on diffusion process 😎Review https://t.ly/F_0Ov 😎Paper arxiv.org/pdf/2310.08580.pdf 😎Project neu-vi.github.io/omnicontrol/

📊 TextPSG: PSG from Text 📊 👉A novel problem in #AI: Panoptic Scene Graph Generation from Purely Textual Descriptions (Capt
📊 TextPSG: PSG from Text 📊 👉A novel problem in #AI: Panoptic Scene Graph Generation from Purely Textual Descriptions (Caption-toPSG) 😎Review https://t.ly/UXEmk 😎Paper arxiv.org/pdf/2310.07056.pdf 😎Project vis-www.cs.umass.edu/TextPSG 😎Code github.com/chengyzhao/TextPSG

🏊 SwimXYZ: Synthetic Swimming 🏊 👉SwimXYZ: synthetic dataset for swimming, monocular videos annotated with ground truth 2D
🏊 SwimXYZ: Synthetic Swimming 🏊 👉SwimXYZ: synthetic dataset for swimming, monocular videos annotated with ground truth 2D and 3D joints

💚💙 Where Is OpenCV 5? 💙💚 👉On October 24th, the organization is launching a crowdfunding campaign to raise funds for #OpenCV 5 development. 👆me in 2005 during my thesis work about face tracking; up to 50x faster than the previous SOTA. No chance to did it without OpenCV library and support from the community. 🔥Support #OpenCV 5 to create the next-gen of researchers and scientists. More: https://t.ly/UTukV

🔥Visual-Math Q&A: MathVista is out! 🔥 👉 MathVista is the ultimate benchmark designed to amalgamate challenges from diverse
🔥Visual-Math Q&A: MathVista is out! 🔥 👉 MathVista is the ultimate benchmark designed to amalgamate challenges from diverse mathematical and visual tasks 😎Review https://t.ly/yfqHZ 😎Paper https://arxiv.org/pdf/2310.02255.pdf 😎Project https://mathvista.github.io/ 😎Code github.com/lupantech/MathVista

🌱 Making LLaMA See and Draw 🌱 👉Tencent #AI planted a SEED of Vision in Large Language Model. Making LLaMA see 'n' draw stuff. 😎Review https://t.ly/QiCAv 😎Paper arxiv.org/pdf/2310.01218.pdf 😎Code github.com/AILab-CVC/SEED