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 17 262 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 491-o'rinni va Malayziya mintaqasida 2 128-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 17 262 obunachiga ega bo‘ldi.
23 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 255 ga, so‘nggi 24 soatda esa 2 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 18.93% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 7.17% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 3 267 marta ko‘riladi; birinchi sutkada odatda 1 237 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 20 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 24 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.
17 262
Obunachilar
+224 soatlar
+67 kun
+25530 kun
Postlar arxiv
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Thanks,
A.
🫛TMR: Few-Shot Template-matching🫛
👉POSTECH unveils TMR, a novel and simple template-matching detector for few-shot pattern detection, achieving strong (and SOTA) results on diverse datasets. A new dataset (RPINE) released, repo soon💙
👉Review https://t.ly/WWAcL
👉Paper https://lnkd.in/dJbSu5vk
👉Project https://lnkd.in/dwcDnHHQ
👉Repo https://lnkd.in/dp7aw8Cs
🪴 Pixie: Physics from Pixels 🪴
👉UPenn + MIT unveil Pixie: training a neural-net that maps pretrained visual features (i.e., CLIP) to dense material fields of physical properties in a single forward pass, enabling real‑time physics simulations. Repo & Dataset under MIT license💙
👉Review https://t.ly/1W0n5
👉Paper https://lnkd.in/dsHAHDqM
👉Project https://lnkd.in/dwrHRbRc
👉Repo https://lnkd.in/dy7bvjsK
❤️🔥PHD: Personalized 3D Humans❤️🔥
👉ETH & #Meta unveil PHD, a novel approach for personalized 3D human mesh recovery (HMR) and body fitting that leverages user-specific shape information to improve pose estimation accuracy. Code & models to be released💙
👉Review https://t.ly/IeRhH
👉Paper https://arxiv.org/pdf/2508.21257
👉Project https://phd-pose.github.io/
👉Repo TBA
🌈 Multi-View 3D Tracking 🌈
👉MVTracker is the first data-driven multi-view 3D point tracker for tracking arbitrary 3D points across multiple cameras. Repo available💙
👉Review https://t.ly/rISMR
👉Paper arxiv.org/pdf/2508.21060
👉Project https://lnkd.in/drHtAmRC
👉Repo https://lnkd.in/d4k8mg3B
🉐Dress&Dance: Dress-up & Dance🉐
👉Dress&Dance: diffusion framework that generates HQ 5-second-long 24 FPS VTON videos at 1152×720 of a user wearing desired garments while moving in accordance with a given reference video. Impressive results but no repo announced🥺
👉Review https://t.ly/7NeTL
👉Paper https://arxiv.org/pdf/2508.21070
👉Project https://immortalco.github.io/DressAndDance/
👉Repo 🥺
🌹ROSE: Remove Objects & Effects🌹
👉A novel framework that systematically fix the object’s effects on environment: shadows, reflections, light, translucency and mirror. Model, Demo & Dataset available via Hugging Face💙
👉Review https://t.ly/_KFM0
👉Paper https://lnkd.in/dNcTXQAE
👉Project https://lnkd.in/dFGmYT5h
👉Model https://lnkd.in/dhTT-VkN
👉Demo https://lnkd.in/dimgXZT6
👉Data https://lnkd.in/da7Jv667
⚽SoccerNet 2025 results are out!⚽
👉SoccerNet 2025 Challenges is the open benchmarking dedicated to advancing computer vision research in football video understanding. Repo for training & Dataset💙
👉Review https://t.ly/MfHKg
👉Paper https://arxiv.org/pdf/2508.19182
👉Project https://www.soccer-net.org/
👉Repo https://github.com/SoccerNet
🥶 OmniHuman-1.5 🥶
👉#ByteDance proposes a novel framework designed to generate character animations that are not only physically plausible but also semantically coherent and expressive. Coherency with speech's rhythm, prosody and semantic content. Impressive results but no code 🥺
👉Review https://t.ly/CnRmX
👉Paper arxiv.org/pdf/2508.19209
👉Project omnihuman-lab.github.io/v1_5/
👉Repo 🥺
🏎️ VROOM: F1 Reconstruction🏎️
👉Berkeley unveils VROOM, the first attempt for reconstructing 3D models of #Formula1 circuits using only onboard camera footage from racecars. Extreme challenges due to noise & speed. Repo released💙
👉Review https://t.ly/uuHdT
👉Paper arxiv.org/pdf/2508.17172
👉Repo github.com/yajatyadav/vroom
👉Project varun-bharadwaj.github.io/vroom/
🧤Diffusive Hand from Signs🧤
👉LIGM + #NVIDIA unveil a novel generative model of 3D hand motions from Sign Language Data. Motion characteristics such as handshapes, locations, finger, hand & arm movements. Code, Models & Data to be released 💙
👉Review https://t.ly/HonX_
👉Paper https://arxiv.org/pdf/2508.15902
👉Project https://imagine.enpc.fr/~leore.bensabath/HandMDM/
👉Data drive.google.com/drive/u/1/folders/1BLsu2hAqhAJ_gnGb9TNXW7MLiSuSEzEj
👉Repo TBA
🫔ATLAS: SOTA Human Model🫔
👉#META presents ATLAS, a novel high-fidelity body model learned from 600k high-res. scans captured using 240 synchronized cams. Code announced, to be released💙
👉Review https://t.ly/0hHud
👉Paper https://arxiv.org/pdf/2508.15767
👉Project https://jindapark.github.io/projects/atlas/
👉Repo TBA
🔬Intern-S1: SOTA MM-MoE 🔬
👉InternS1: a MM-MoE with 28B activated / 241b total parameters, continually pre-trained on 5T tokens, including 2.5T+ tokens from scientific domains. New SOTA for professional tasks, such as molecular synthesis planning, reaction condition prediction, etc. Models available under Apache 2.0💙
👉Review https://t.ly/3l5UW
👉Paper arxiv.org/pdf/2508.15763
👉Repo github.com/InternLM/Intern-S1
🤗HF huggingface.co/internlm/Intern-S1
🧉 YOPO: SOTA 9-DoF Pose🧉
👉Pit In Co. unveils YOPO, a novel single-stage, query-based framework that treats category-level 9-DoF estimation as a natural extension of 2D detection. A practical solution for mono-RGB, category-level, multi-obj pose estimation. Code & models announced (coming)💙
👉Review https://t.ly/cf_Cl
👉Paper https://arxiv.org/pdf/2508.14965
👉Project mikigom.github.io/YOPO-project-page/
👉Repo TBA
📡 ROVR Open Dataset is out 📡
👉A novel large-scale open 3D dataset for autonomous driving, robotics, and 4D perception tasks. To be released for academic (for free) & commercial💙
👉Review https://t.ly/iDcvg
👉Paper https://arxiv.org/pdf/2508.13977
👉Project https://xiandaguo.net/ROVR-Open-Dataset
👠 OmniTry: Virtual Try-On Anything 👠
👉OmniTry: unified framework that extends VTON beyond garment to encompass any wearable objects (jewelries, accessories, etc.) in mask-free setting. Weights, HF demo & benchmark released💙
👉Review https://t.ly/wMBGQ
👉Paper https://lnkd.in/dQe9MchS
👉Project https://omnitry.github.io/
👉Repo https://lnkd.in/d3QwAXY2
🤗Demo https://lnkd.in/duUcZpVA
🌈DAViD: Synthetic Depth-Normal-Segmentation🌈
👉#Microsoft unveils DAViD: 100% synthetic dataset/models for human Depth, Normals & Segmentation. Impressive results at a fraction of the cost of the foundation models! Compliancy with privacy, copyright, licensing, and diversity requirements. Dataset available, models & runtime under MIT💙
👉Review https://t.ly/-SlO_
👉Paper https://lnkd.in/eCmMXpTg
👉Project https://lnkd.in/eurCSWkm
👉Repo https://lnkd.in/e7PWFgP2
🔀4DNeX: Feed-Forward 4D video🔀
👉4DNeX is the first feed-forward framework for generating 4D scene representations from a single image by fine-tuning diffusion model. HQ dynamic pt-clouds & downstream tasks such as novel-view video synthesis with strong generalizability. Code/Data announced 💙
👉Review https://t.ly/SpkD-
👉Paper arxiv.org/pdf/2508.13154
👉Project https://4dnex.github.io/
👉Repo github.com/3DTopia/4DNeX
👉Data https://lnkd.in/dh4_3Ghf
👉Demo https://lnkd.in/dztyzwgg
🏓TOTNet: Occlusion-aware Tracking🏓
👉TOTNet is a novel Temporal Occlusion Tracking Network that leverages 3D-convs, visibility-weighted loss, & occlusion augmentation to improve performance under occlusions. Code & Data available under MIT💙
👉Review https://t.ly/Q0jAf
👉Paper https://lnkd.in/dUYsa-GC
👉Repo https://lnkd.in/d3QGUHYb
🤖 Impact of SuperHuman AI 🤖
👉The NoProfit AI Futures Project unveils a (dystopic) scenario about what super-AI might look like. Forecast from today to the bio-engineered human-like creatures. A fascinating speculation of the future with the "slow-down" and "race" scenarios. Enjoy 💙
👉Review https://t.ly/EgmfJ
👉Project https://ai-2027.com/
