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AI with Papers - Artificial Intelligence & Deep Learning

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

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 17 261 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 543-o'rinni va Malayziya mintaqasida 2 144-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 17 261 obunachiga ega bo‘ldi.

26 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 250 ga, so‘nggi 24 soatda esa 1 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 17.43% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 7.04% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 3 008 marta ko‘riladi; birinchi sutkada odatda 1 216 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 16 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 27 Oktabr, 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.

17 261
Obunachilar
+124 soatlar
+97 kun
+25030 kun
Postlar arxiv
🪛 HANDAL: Real-World Manipulable Objects 🪛 👉 #Nvidia unveils HANDAL dataset: category-level object pose and affordance prediction 😎Review https://t.ly/MXZDI 😎Paper arxiv.org/pdf/2308.01477.pdf 😎Dataset https://wenbowen123.github.io/handaldataset/

🙏 A quick poll for helping me in improving the quality of the contents about #computervision. Please give me a feedback here: https://t.ly/qXb4C Thanks :)

🎠 Neural Closed-Loop Simulator 🎠 👉A neural sensor simulator that takes a single recorded log captured by a sensor-equipped vehicle and converts it into a realistic closed-loop multi-sensor simulation 😎Review https://t.ly/EcRLc 😎Paper arxiv.org/pdf/2308.01898.pdf 😎Project https://waabi.ai/unisim/

📸 Computational Burst Photography in App 📸 👉#Google unveils a novel computational burst system to democratize the professional photography via smartphone 😎Review https://t.ly/5ibJX 😎Paper arxiv.org/pdf/2308.01379.pdf 😎Project https://motion-mode.github.io

👗 Multimodal Neural Designer 👗 👉 Multimodal #AI that can generate novel fashion images conditioned on text, keypoints, and sketches 😎Review https://t.ly/zVk70 😎Paper arxiv.org/pdf/2304.02051.pdf 😎Code github.com/aimagelab/multimodal-garment-designer

🥬 Consensus-Adaptive RANSAC 🥬 👉A novel RANSAC that learns to explore the parameter space via a novel attention layer 😎Rev
🥬 Consensus-Adaptive RANSAC 🥬 👉A novel RANSAC that learns to explore the parameter space via a novel attention layer 😎Review https://t.ly/eSLmD 😎Paper arxiv.org/pdf/2307.14030.pdf 😎Code github.com/cavalli1234/CA-RANSAC

🥬 Consensus-Adaptive RANSAC 🥬 👉A novel RANSAC that learns to explore the parameter space via a novel attention layer

🐧 Tracking Anything in High Quality 🐧 👉Video multi-object segmenter (VMOS) and a mask refiner (MR) to track anything 😎Review https://t.ly/hAvF2 😎Paper arxiv.org/pdf/2307.13974.pdf 😎Code github.com/jiawen-zhu/HQTrack

🦀 simPLE: learning to grasp only with CAD 🦀 👉simPLE learns to pick, regrasp & place objects precisely, given only the object CAD model and no prior experience 😎Review https://t.ly/ab5pA 😎Paper arxiv.org/pdf/2307.13133.pdf 😎Project mcube.mit.edu/research/simPLE.html

🥬 Generative AI’s Next Frontiers 🥬 👉Hair simulation, 2D->3D animation, and much more. ~20 papers from #NVIDIA accepted into #SIGGRAPH2023 😎 Review https://t.ly/wgGin

🛵ALPR via CTS-Matching 🛵 👉UIT unveils a neural approach (#YOLO5 + tracking + rotation) to improve the license plate recognition accuracy 😎Review https://t.ly/VP4BP 😎Paper arxiv.org/pdf/2307.11336.pdf 😎Code github.com/chequanghuy/Character-Time-series-Matching

🪛 CAD-based Object Segmentation 🪛 👉 A novel three-stage approach to segment unseen objects in RGB images using their CAD models 😎Review https://t.ly/RtHLN 😎Paper arxiv.org/pdf/2307.11067.pdf 😎Code https://github.com/nv-nguyen/cnos

🪤 PAPR: Proximity Attention Point Render 🪤 👉PAPR: fast point-based scene representation with differentiable renderer approach 😎Review https://t.ly/yoI0g 😎Paper arxiv.org/pdf/2307.11086.pdf 😎Project https://zvict.github.io/papr

🪤 PAPR: Proximity Attention Point Render 🪤 👉PAPR: fast point-based scene representation with differentiable renderer approach

💪 Muscles in Action with #AI 💪 👉Muscles in Action (MIA): learn to incorporate muscle activity into human motion representations 😎Review https://t.ly/hUKub 😎Paper arxiv.org/pdf/2212.02978.pdf 😎Project musclesinaction.cs.columbia.edu

👩‍🦰 Ultra-Realistic Neural Hair 👩‍🦰 👉A novel method to reconstruct the hair geometry at a strand level from monocular video or multi-view images 😎Review https://t.ly/6xZyp 😎Paper arxiv.org/pdf/2306.05872.pdf 😎Project samsunglabs.github.io/NeuralHaircut 😎Code github.com/SamsungLabs/NeuralHaircut

🪟 META's Ultra-Realistic Data for #AR🪟 👉Aria Digital Twin: egocentric dataset for object detection/tracking, reconstruction/understanding, S2R learning, human pose prediction and more 😎Review https://t.ly/MRPt1 😎Paper arxiv.org/pdf/2306.06362.pdf 😎Project www.projectaria.com/datasets/adt/ 😎Code github.com/facebookresearch/projectaria_tools

🍉 AltFreezing: new SOTA in detecting fake-faces 🍉 👉#Microsoft unveils AltFreezing: spatial/temporal artifacts in one model for more general face forgery detection 😎Review https://t.ly/mkIKX 😎Paper https://t.ly/z4KnJ 😎Code github.com/ZhendongWang6/AltFreezing

🦙 Llama-2: the Open-Source "#chatgpt"🦙 👉GenAI, #Meta unveils Llama-2: a collection of LLMs ranging in scale 7-70B paramete
🦙 Llama-2: the Open-Source "#chatgpt"🦙 👉GenAI, #Meta unveils Llama-2: a collection of LLMs ranging in scale 7-70B parameters. Challenging with #chatgpt, but open. 😎Review https://t.ly/bLJgP 😎Paper https://t.ly/AOXru 😎Project https://ai.meta.com/research/publications/llama-2-open-foundation-and-fine-tuned-chat-models/