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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

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AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 17 154 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 726-o'rinni va Malayziya mintaqasida 2 240-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 17 154 obunachiga ega bo‘ldi.

21 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -166 ga, so‘nggi 24 soatda esa -6 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 23.63% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 6.86% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 4 057 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.

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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 22 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.

17 154
Obunachilar
-624 soatlar
-277 kunlar
-16630 kunlar
Postlar arxiv
🥎POKEFLEX: Soft Object Dataset🥎 👉PokeFlex from ETH is a dataset that includes 3D textured meshes, point clouds, RGB & depth maps of deformable objects. Pretrained models & dataset announced💙 👉Review https://t.ly/GXggP 👉Paper arxiv.org/pdf/2410.07688 👉Project https://lnkd.in/duv-jS7a 👉Repo

💡Diffusion Models Relighting💡 👉#Netflix unveils DifFRelight, a novel free-viewpoint facial relighting via diffusion model. Precise lighting control, high-fidelity relit facial images from flat-lit inputs. 👉Review https://t.ly/fliXU 👉Paper arxiv.org/pdf/2410.08188 👉Project www.eyelinestudios.com/research/diffrelight.html

🥦Gaussian Splatting VTON🥦 👉GS-VTON is a novel image-prompted 3D-VTON which, by leveraging 3DGS as the 3D representation, enables the transfer of pre-trained knowledge from 2D VTON models to 3D while improving cross-view consistency. Code announced💙 👉Review https://t.ly/sTPbW 👉Paper arxiv.org/pdf/2410.05259 👉Project yukangcao.github.io/GS-VTON/ 👉Repo github.com/yukangcao/GS-VTON

🐏 EFM3D: 3D Ego-Foundation 🐏 👉#META presents EFM3D, the first benchmark for 3D object detection and surface regression on HQ annotated egocentric data of Project Aria. Datasets & Code released💙 👉Review https://t.ly/cDJv6 👉Paper arxiv.org/pdf/2406.10224 👉Project www.projectaria.com/datasets/aeo/ 👉Repo github.com/facebookresearch/efm3d

🔥 "Deep Gen-AI" Full Course 🔥 👉A fresh course from Stanford about the probabilistic foundations and algorithms for deep ge
🔥 "Deep Gen-AI" Full Course 🔥 👉A fresh course from Stanford about the probabilistic foundations and algorithms for deep generative models. A novel overview about the evolution of the genAI in #computervision, language and more... 👉Review https://t.ly/ylBxq 👉Course https://lnkd.in/dMKH9gNe 👉Lectures https://lnkd.in/d_uwDvT6

🛳️ EVER Ellipsoid Rendering 🛳️ 👉UCSD & Google present EVER, a novel method for real-time differentiable emission-only volume rendering. Unlike 3DGS it does not suffer from popping artifacts and view dependent density, achieving ∼30 FPS at 720p on #NVIDIA RTX4090. 👉Review https://t.ly/zAfGU 👉Paper arxiv.org/pdf/2410.01804 👉Project half-potato.gitlab.io/posts/ever/

🦴 One-Image Object Detection 🦴 👉Delft University (+Hensoldt Optronics) introduces OSSA, a novel unsupervised domain adaptation method for object detection that utilizes a single, unlabeled target image to approximate the target domain style. Code released💙 👉Review https://t.ly/-li2G 👉Paper arxiv.org/pdf/2410.00900 👉Code github.com/RobinGerster7/OSSA

🍇SPARK: Real-time Face Capture🍇 👉Technicolor Group unveils SPARK, a novel high-precision 3D face capture via collection of unconstrained videos of a subject as prior information. New SOTA able to handle unseen pose, expression and lighting. Impressive results. Code & Model announced💙 👉Review https://t.ly/rZOgp 👉Paper arxiv.org/pdf/2409.07984 👉Project kelianb.github.io/SPARK/ 👉Repo github.com/KelianB/SPARK/

👩‍🦰 SOTA Gaussian Haircut 👩‍🦰 👉ETH et. al unveils Gaussian Haircut, the new SOTA in hair reconstruction via dual representation (classic + 3D Gaussian). Code and Model announced💙 👉Review https://t.ly/aiOjq 👉Paper arxiv.org/pdf/2409.14778 👉Project https://lnkd.in/dFRm2ycb 👉Repo https://lnkd.in/d5NWNkb5

🌾 New SOTA Edge Detection 🌾 👉CUP (+ ESPOCH) unveils the new SOTA for Edge Detection (NBED); superior performance consistently across multiple benchmarks, even compared with huge computational cost and complex training models. Source Code released💙 👉Review https://t.ly/zUMcS 👉Paper arxiv.org/pdf/2409.14976 👉Code github.com/Li-yachuan/NBED

🩰 Dressed Humans in the wild 🩰 👉ETH (+ #Microsoft ) ReLoo: novel 3D-HQ reconstruction of humans dressed in loose garments from mono in-the-wild clips. No prior assumptions about the garments. Source Code announced, coming 💙 👉Review https://t.ly/evgmN 👉Paper arxiv.org/pdf/2409.15269 👉Project moygcc.github.io/ReLoo/ 👉Code github.com/eth-ait/ReLoo

🎢 Robo-quadruped Parkour🎢 👉LAAS-CNRS unveils a novel RL approach to perform agile skills that are reminiscent of parkour, such as walking, climbing high steps, leaping over gaps, and crawling under obstacles. Data and Code available💙 👉Review https://t.ly/-6VRm 👉Paper arxiv.org/pdf/2409.13678 👉Project gepetto.github.io/SoloParkour/ 👉Code github.com/Gepetto/SoloParkour

🌏 JoyHallo: Mandarin Digital Human 🌏 👉JD Health faced the challenges of audio-driven video generation in Mandarin, a task complicated by the language’s intricate lip movements and the scarcity of HQ datasets. Impressive results (-> audio ON). Code Models available💙 👉Review https://t.ly/5NGDh 👉Paper arxiv.org/pdf/2409.13268 👉Project jdh-algo.github.io/JoyHallo/ 👉Code github.com/jdh-algo/JoyHallo

🌏 JoyHallo: Mandarin Digital Human 🌏 👉JD Health faced the challenges of audio-driven video generation in Mandarin, a task complicated by the language’s intricate lip movements and the scarcity of HQ datasets. Impressive results (-> audio ON). Code Models available💙 👉Review 👉Paper arxiv.org/pdf/2409.13268 👉Project jdh-algo.github.io/JoyHallo/ 👉Code github.com/jdh-algo/JoyHallo

⚽ SoccerNet 2024 Results ⚽ 👉SoccerNet is the annual video understanding challenge for football. These challenges aim to advance research across multiple themes in football. The 2024 results are out! 👉Review https://t.ly/DUPgx 👉Paper arxiv.org/pdf/2409.10587 👉Repo github.com/SoccerNet 👉Project www.soccer-net.org/

🧸Motion Instruction Fine-Tuning🧸 👉MotIF is a novel method that fine-tunes pre-trained VLMs to equip the capability to distinguish nuanced robotic motions with different shapes and semantic groundings. A work by MIT, Stanford, and CMU. Source Code announced, coming💙 👉Review https://t.ly/iJ2UY 👉Paper https://arxiv.org/pdf/2409.10683 👉Project https://motif-1k.github.io/ 👉Code coming

🌭Hand-Object interaction Pretraining🌭 👉Berkeley unveils HOP, a novel approach to learn general robot manipulation priors from 3D hand-object interaction trajectories. 👉Review https://t.ly/FLqvJ 👉Paper https://arxiv.org/pdf/2409.08273 👉Project https://hgaurav2k.github.io/hop/

💄Interactive Drag-based Editing💄 👉CSE unveils InstantDrag: novel pipeline designed to enhance editing interactivity and speed, taking only an image and a drag instruction as input. Source Code announced, coming💙 👉Review https://t.ly/hy6SL 👉Paper arxiv.org/pdf/2409.08857 👉Project joonghyuk.com/instantdrag-web/ 👉Code github.com/alex4727/InstantDrag

🫒 Omni Urban Scene Reconstruction 🫒 👉OmniRe is novel holistic approach for efficiently reconstructing HD dynamic urban scenes from on-device logs. It's able to create the simulation of reconstructed scenarios with actors in real-time (~60 Hz). Code released💙 👉Review https://t.ly/SXVPa 👉Paper arxiv.org/pdf/2408.16760 👉Project ziyc.github.io/omnire/ 👉Code github.com/ziyc/drivestudio

🐺 Diffusion Game Engine 🐺 👉#Google unveils GameNGen: the first game engine powered entirely by a neural #AI that enables real-time interaction with a complex environment over long trajectories at HQ. No code announced but I love it 💙 👉Review https://t.ly/_WR5z 👉Paper https://lnkd.in/dZqgiqb9 👉Project https://lnkd.in/dJUd2Fr6

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