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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 17 137 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, 17 137 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.
17 137
Obunachilar
-724 soatlar
-427 kunlar
-19730 kunlar
Postlar arxiv
💘 3D-aware Blending via Generative NeRF 💘
👉Novel 3D-aware blending method via generative NeRFs
😎Review https://bit.ly/3lBEJA2
😎Paper arxiv.org/pdf/2302.06608.pdf
😎Project blandocs.github.io/blendnerf
😎Code github.com/naver-ai/BlendNeRF
🥸 MEGANE: Generative Morphable Eyeglass 🥸
👉#META unveils the most advanced #3D compositional morphable AI for eyeglasses (HD geometry/photometric interaction)
😎Review https://bit.ly/3jOWifu
😎Paper arxiv.org/pdf/2302.04868.pdf
😎Project junxuan-li.github.io/megane
🎃 In-N-Out: 3D-aware OOD video editing 🎃
👉Novel 3D-aware video editing able to manipulate OOD objects (e.g. heavy makeup, accessories)
😎Review https://bit.ly/3jN0CMu
😎Paper arxiv.org/pdf/2302.04871.pdf
😎Project https://in-n-out-3d.github.io
🧱 LEGO-Net: Objects in Rooms 🧱
👉Transformer-based iterative method for rearrangement of objects in messy rooms
😎Review https://bit.ly/3HR0fs6
😎Paper arxiv.org/pdf/2301.09629.pdf
😎Project ivl.cs.brown.edu/#/projects/lego-net
🗿DirectMHP: Multi-Head Pose Estimation🗿
👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles
😎Review https://bit.ly/3HJubXg
😎Paper arxiv.org/pdf/2302.01110.pdf
😎Code github.com/hnuzhy/DirectMHP
🗿DirectMHP: Multi-Head Pose Estimation🗿
👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles
😎Review https://bit.ly/3HJubXg
😎Paper arxiv.org/pdf/2302.01110.pdf
😎Code github.com/hnuzhy/DirectMHP
🗿DirectMHP: Multi-Head Pose Estimation🗿
👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles
🌘 Gen-1: next-gen Generative #AI 🌘
👉#Runaway unveils Gen-1: the next step forward for Generative AI. Registration available for beta -> hurry up!
😎Review https://bit.ly/3YqQYh8
😎Project https://research.runwayml.com/gen1
🦚 MOSE: coMplex video Object SEgmentation 🦚
👉Novel Dataset for VOS is out! SOTA method on DAVIS is only 59.4% on MOSE
😎Review https://bit.ly/40yzSzW
😎Paper arxiv.org/pdf/2302.01872.pdf
😎Project henghuiding.github.io/MOSE/
😎Code github.com/henghuiding/MOSE-api
🧩 Text-Guided #3D Texturing 🧩
👉 Text-Guided HQ textures via iterative diffusion-based process
😎Review https://bit.ly/3ldC6Ez
😎Project texturepaper.github.io/TEXTurePaper
😎Code github.com/TEXTurePaper/TEXTurePaper
😎Paper texturepaper.github.io/TEXTurePaper/static/paper.pdf
🐓 DREAMIX: General Diffusion Video Editors 🐓
👉#Google unveils the first diffusion-based method able to perform text-based motion/appearance editing of general videos
😎Review https://bit.ly/3I3Hq6B
😎Paper arxiv.org/pdf/2302.01329.pdf
😎Project dreamix-video-editing.github.io/
💧FLOW360: 360° Neural Optical Flow💧
👉 IIT unveils the first perceptually realistic 360° video benchmark dataset + SLOF method for OF tracking
😎Review https://bit.ly/3wMZZoX
😎Paper arxiv.org/pdf/2301.11880.pdf
😎Project https://siamlof.github.io
🛋️🛋️ 100% Accurated #3D Labeling 🛋️🛋️
👉#Amazon unveils a novel tool for fine-grained 3D part labeling. Up to 100% accuracy! Paper (only😢)
😎Review https://bit.ly/3kYpQHQ
😎Paper https://arxiv.org/pdf/2301.10460.pdf
⭐ Mono-STAR: Unified Tracking/Reconstruction ⭐
👉Real-time 3D unified framework for semantic fusion, tracking, non-rigid deformation, and topological changes
😎Review https://bit.ly/3Dxvxmx
😎Paper arxiv.org/pdf/2301.13244.pdf
😎Project github.com/changhaonan/Mono-STAR-demo
🚛 Text-driven Video Neural Editing 🚛
👉A novel text-guided video editing with both appearance/shape
😎Review https://bit.ly/3YcfMJO
😎Paper arxiv.org/pdf/2301.13173.pdf
😎Project text-video-edit.github.io/
🎷Audio-Visual Semantic Segmentation🎷
👉A novel problem in #AI: pixel-level segmentation of objects that produce sound in the image frame
😎Review https://bit.ly/3wFY6dw
😎Paper arxiv.org/pdf/2301.13190.pdf
😎Project opennlplab.github.io/AVSBench
😎Code github.com/OpenNLPLab/AVSBench
🐦 PhyCV: Physics-inspired Computer Vision 🐦
👉From UCLA, the first Physics-inspired Computer Vision Library
😎Review https://bit.ly/3HEWozI
😎Code github.com/JalaliLabUCLA/phycv
😎Project photonics.ucla.edu/2022/05/12/jalali-lab-open-sources-phycv-a-physics-inspired-computer-vision-library/
😍 CLIP/GPT3-driven Affective Faces 😍
👉Columbia unveils a novel framework for facial expressions retrieval given the context of the speaker
😎Review https://bit.ly/3HERna0
😎Paper arxiv.org/pdf/2301.10939.pdf
😎Project realtalk.cs.columbia.edu
😎Code github.com/scottgeng00/realtalk
🔥CutLER: Unsupervised Segmentation 🔥
👉Novel paper by #META on detection & instance segmentation without human annotations
😎Review https://bit.ly/3DlFiUG
😎Paper arxiv.org/pdf/2301.11320.pdf
😎Code github.com/facebookresearch/CutLER
😎Project people.eecs.berkeley.edu/~xdwang/projects/CutLER
🐕 MAV3D: #3D Video from Text 🐕
👉#META unveils a novel #AI for generating #3D dynamic videos from text
😎Review https://bit.ly/3WPRAvK
😎Paper arxiv.org/pdf/2301.11280.pdf
😎Project make-a-video3d.github.io
