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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 17 145 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 702-o'rinni va Malayziya mintaqasida 2 235-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 17 145 obunachiga ega bo‘ldi.
24 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -197 ga, so‘nggi 24 soatda esa -7 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 25.73% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 6.87% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 4 411 marta ko‘riladi; birinchi sutkada odatda 1 177 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 26 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 25 Iyun, 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.
17 145
Obunachilar
-724 soatlar
-427 kunlar
-19730 kunlar
Postlar arxiv
🔥New SOTA in Panoptic Segmentation🔥
👉#Google (with Hinton🤯) unveils Pix2Seq-D: novel generalist framework for panoptic segmentation
😎Review https://bit.ly/3DmpbGM
😎Paper arxiv.org/pdf/2210.06366.pdf
🦙LaMAR: Localization/Mapping for #AR🦙
👉A new benchmark for #AR in large and unconstrained scenes
😎Review https://bit.ly/3DjlnWU
😎Paper lamar.ethz.ch/files/LaMAR.pdf
😎Project https://lamar.ethz.ch/
😎Code github.com/microsoft/lamar-benchmark
🪂 Parallel NeRF for 6-DoF pose 🪂
👉#Nvidia unveils a parallel NeRF for 6-DoF target pose estimation
😎Review https://bit.ly/3guWWwA
😎Paper arxiv.org/pdf/2210.10108.pdf
😎Project https://pnerfp.github.io/
🔥Meta Omni3D: code is out!🔥
👉Source Code, models, and data just released by #META !
😎Review https://bit.ly/3MIWxD9
😎Paper arxiv.org/pdf/2207.10660.pdf
😎Project garrickbrazil.com/omni3d/
😎Code github.com/facebookresearch/omni3d
🔥 Dressing Avatars by #META 🔥
👉Novel deep photorealistic appearance method for physically-simulated clothing in #metaverse
😎Review https://bit.ly/3yRBW9Y
😎Paper arxiv.org/pdf/2206.15470.pdf
⚽Markerless Body-Object Interaction⚽
👉Novel whole-bodies/objects interaction method from multi-view RGB-D data
😎Review https://bit.ly/3yO56GY
😎Data intercap.is.tue.mpg.de/login.php
😎Project https://intercap.is.tue.mpg.de
😎Code github.com/YinghaoHuang91
😎Paper intercap.is.tue.mpg.de/media/upload/main.pdf
⛽ Stable Diffusion in #Blender ⛽
👉Render with SuperPowers: novel scene render via text prompt
😎Review https://bit.ly/3s1mEeN
😎Code github.com/benrugg/AI-Render
🪲#6D estimation fully in the wild🪲
👉First ever self-supervised 6D pose estimation training in the wild
😎Review https://bit.ly/3yHdHuS
😎Paper arxiv.org/pdf/2210.07199.pdf
😎Project kywind.github.io/self-pose
😎Code (soon)
🧮 Novel DM for 3D Shapes by #Nvidia 🧮
👉Hierarchical Latent Point Diffusion Model (LION) for 3D shape generation
😎Review https://bit.ly/3yDhZ6I
😎Paper arxiv.org/pdf/2210.06978.pdf
😎Project https://nv-tlabs.github.io/LION/
😎Code(soon) github.com/nv-tlabs/LION
🦑 Instant Map-free Relocalization 🦑
👉#Niantic unveils a novel instant, metric scaled re-localization with one single photo
😎Review https://bit.ly/3S1Gdyh
😎Paper arxiv.org/pdf/2210.05494.pdf
😎Project research.nianticlabs.com/mapfree-reloc-benchmark
😎Data research.nianticlabs.com/mapfree-reloc-benchmark/dataset
🔥 Matterport 3D Semantics Dataset 🔥
👉#Meta opens HM3DSEM, the largest #3D real-world dataset with dense semantic
😎Review https://bit.ly/3yF4W4G
😎Paper arxiv.org/pdf/2210.05633.pdf
😎Project aihabitat.org/datasets/hm3d-semantics
😎Data github.com/matterport/habitat-matterport-3dresearch
🥬 "Perception Test" by #DeepMind 🥬
👉Huge dataset with obj & point tracks, temporal sounds, multiple & grounded vQA
😎Review https://bit.ly/3Vqh96Q
😎Dataset github.com/deepmind/perception_test
😎Project www.deepmind.com/blog/measuring-perception-in-ai-models
🏅GENIE by #Nvidia -> Faster Generation🏅
👉Higher-Order Denoising Diffusion Solvers for faster and better synthesis
😎Review https://bit.ly/3CRjtwr
😎Project nv-tlabs.github.io/GENIE/
😎Paper arxiv.org/pdf/2210.05475.pdf
😎Code github.com/nv-tlabs/GENIE
🍏 f-DM: Diffusion Models by Apple 🍏
👉Spectacular work by #Apple on DMs: HQ generation with better efficiency and semantic
😎Review https://bit.ly/3Tils2u
😎Project https://jiataogu.me/fdm/
😎Paper arxiv.org/pdf/2210.04955.pdf
🥏 EVA3D: new SOTA in #3D humans 🥏
👉EVA3D: new SOTA for unconditional NeRF-human generation from 2D only
😎Review https://bit.ly/3Th9qX7
😎Code github.com/hongfz16/EVA3D
😎Paper arxiv.org/pdf/2210.04888.pdf
😎Project hongfz16.github.io/projects/EVA3D.html
🔥SIMPLI: ligh novel-view synthesis🔥
👉Lightweight novel-view synthesis by #Samsung for arbitrary forward-facing scenes
😎Review https://bit.ly/3CivSYZ
😎Project samsunglabs.github.io/MLI
😎Code github.com/SamsungLabs/MLI
😎Paper samsunglabs.github.io/MLI/paper/paper.pdf
🍋 Long Video via Transformers 🍋
👉TECO is a vector-quantized latent dynamics prediction for long video
😎Review https://bit.ly/3Ch0tWD
😎Project wilson1yan.github.io/teco/
😎Paper arxiv.org/pdf/2210.02396.pdf
😎Code github.com/wilson1yan/teco
🔥 #AIwithPapers: we are 4,500+! 🔥
💙💛 Someone put the smiling 💩 under a few recent posts. But I still love you! 💙💛
😈 Invite your friends -> https://t.me/AI_DeepLearning
⚛️SOTA ALERT! Particles Tracking ⚛️
👉The new SOTA in video particles tracking. "Old school" taste, with neural flavor 🧡
😎Review https://bit.ly/3CaU5Ai
😎Project particle-video-revisited.github.io/
😎Paper arxiv.org/pdf/2204.04153.pdf
😎Code github.com/aharley/pips
🔥 Human MDM: source code is out! 🔥
👉A classifier-free diffusion-based generative model for human motion domain
😎Review https://bit.ly/3rFhR2G
😎Project guytevet.github.io/mdm-page
😎Paper arxiv.org/pdf/2209.14916.pdf
😎Code github.com/GuyTevet/motion-diffusion-model
