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
Больше📈 Аналитический обзор Telegram-канала AI with Papers - Artificial Intelligence & Deep Learning
Канал AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 17 259 подписчиков, занимая 7 509 место в категории Технологии и приложения и 2 130 место в регионе Малайзия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 17 259 подписчиков.
Согласно последним данным от 25 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 261, а за последние 24 часа — 2, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 16.91%. В первые 24 часа после публикации контент обычно набирает 7.04% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 2 918 просмотров. В течение первых суток публикация набирает 1 216 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 16.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как framework, object, dataset, tba, depth.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“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”
Благодаря высокой частоте обновлений (последние данные получены 26 октября, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.
17 259
Подписчики
+224 часа
+17 дней
+26130 дней
Архив постов
🌵 G-Splatting Controllable Portraits 🌵
👉From monocular/casual video captures, Rig3DGS rigs 3D Gaussian Splatting to enable the creation of re-animatable portrait videos with control over facial expressions, head-pose and viewing direction. Authors: Stony Brook University & #Adobe
👉Review https://t.ly/fq71w
👉Paper https://arxiv.org/pdf/2402.03723.pdf
👉Project shahrukhathar.github.io/2024/02/05/Rig3DGS.html
🪵 HASSOD Object Detection 🪵
👉 HASSOD: fully self-supervised detection and instance segmentation. The new SOTA able to understand the part-to-whole object composition like humans do.
👉Review https://t.ly/66qHF
👉Paper arxiv.org/pdf/2402.03311.pdf
👉Project hassod-neurips23.github.io/
👉Repo github.com/Shengcao-Cao/HASSOD
💥 #Py4AI: 2x speakers, 2x tickets! 💥
✅Doubling the speakers (6 -> 12!)
✅Adding a new track (2 tracks in parallel)
✅Releasing a new batch of 100 tickets!
👉 More: https://t.ly/WmVrM
🏇Bootstrapping TAP 🏇
👉#Deepmind shows how large-scale, unlabeled, uncurated real-world data can improve TAP with minimal architectural changes, via a self-supervised student-teacher setup. Source Code released 💙
👉Review https://t.ly/-S_ZL
👉Paper https://arxiv.org/pdf/2402.00847.pdf
👉Code https://lnkd.in/gyi7Dhkn
🍬 ABS: SOTA collision-free 🍬
👉ABS (Agile But Safe): learning-based control framework for agile and collision-free locomotion for quadrupedal robot. Source Code announced (coming) 💙
👉Review https://t.ly/AYu-Z
👉Paper arxiv.org/pdf/2401.17583.pdf
👉Project agile-but-safe.github.io/
👉Repo github.com/LeCAR-Lab/ABS
🚦(adding) Anything in Any Video🚦🚦
👉 XPeng Motors announced Anything in Any Scene: novel #AI for realistic video simulation that seamlessly inserts any object into an existing dynamic video. Strong emphasis on realism, the objects in the BBs don't exist. Source Code released 💙
👉Review https://t.ly/UYhl0
👉Code https://lnkd.in/gyi7Dhkn
👉Paper https://lnkd.in/gXyAJ6GZ
👉Project https://lnkd.in/gVA5vduD
🚦(adding) Anything in Any Video🚦🚦
👉 XPeng Motors announced Anything in Any Scene: novel #AI for realistic video simulation that seamlessly inserts any object into an existing dynamic video. Strong emphasis on realism, the objects in the BBs don't exist. Source Code released 💙
👉Review https://t.ly/UYhl0
👉Code https://lnkd.in/gyi7Dhkn
👉Paper https://lnkd.in/gXyAJ6GZ
👉Project https://lnkd.in/gVA5vduD
🎉 ADΔER: Event-Camera Suite 🎉
👉ADΔER: a novel/unified framework for event-based video. Encoder / transcoder / decoder for ADΔER (Address, Decimation, Δt Event Representation) video streams. Source code (RUST) released 💙 H/T author: Andrew C. Freeman from University of North Carolina, USA.
👉Review https://t.ly/w5_KC
👉Paper arxiv.org/pdf/2401.17151.pdf
👉Repo github.com/ac-freeman/adder-codec-rs
↘️ SEELE: "moving" the subjects ➡️
👉Subject repositioning: manipulating an input image to reposition one of its subjects to a desired location while preserving the image’s fidelity. SEELE is a single diffusion model to address this novel generative sub-tasks
👉Review https://t.ly/4FS4H
👉Paper https://arxiv.org/pdf/2401.16861.pdf
👉Project https://yikai-wang.github.io/seele/
🥓 RANSAC -> PARSAC (neural) 🥓
👉Neural PARSAC: estimating multiple vanishing points (V), fundamental matrices (F) or homographies (H) at the speed of light! Source Code released 💙
👉Review https://t.ly/r9ngg
👉Paper https://lnkd.in/dadQ4Qec
👉Code https://lnkd.in/dYp6gADd
🍋 Diffutoon: new SOTA video 🍋
👉Diffutoon is a cartoon shading approach, aiming to transform photorealistic videos in anime styles. It can handle exceptionally high resolutions and rapid motions. Source code released!
👉Review https://t.ly/sim2O
👉Paper https://lnkd.in/dPcSnAUu
👉Code https://lnkd.in/d9B_dGrf
👉Project https://lnkd.in/dpcsJcX2
🧠350+ Free #AI Courses by #Google🧠
👉350+ free courses from #Google to become professional in #AI & #Cloud. The full catalog (900+) includes a variety of activity: videos, documents, labs, coding, and quizzes. 15+ supported languages. No excuse.
✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈
✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐋𝐋𝐌𝐬
✅𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐓𝐅
✅𝐁𝐚𝐬𝐞𝐥𝐢𝐧𝐞 𝐃𝐚𝐭𝐚, 𝐌𝐋, 𝐀𝐈
✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐀𝐈
👉Review: https://t.ly/517Dr
👉Full list: https://www.cloudskillsboost.google/catalog?page=1
🐙 Rock-Track announced! 🐙
👉Key Lab of Robotics and System announced Rock-Track, the evolution of Poly-MOT, the previous SOTA in 3D MOT Tracking-By-Detection framework.
👉Review https://t.ly/hC0ak
👉Repo, coming: https://lnkd.in/dtDkPwCC
👉Paper coming
🌋EasyVolcap: Accelerating Neural Volumetric🌋
👉Novel #PyTorch library for accelerating neural volumetric video research: volumetric video capturing, reconstruction & rendering
👉Review https://t.ly/8BISl
👉Paper arxiv.org/pdf/2312.06575.pdf
👉Code github.com/zju3dv/EasyVolcap
🦩 WildRGB-D: Objects in the Wild 🦩
👉#NVIDIA unveils a novel RGB-D object dataset captured in the wild: ~8500 recorded objects, ~20,000 RGBD videos, 46 categories with corresponding masks and 3D point clouds.
👉Review https://t.ly/WCqVz
👉Data github.com/wildrgbd/wildrgbd
👉Paper arxiv.org/pdf/2401.12592.pdf
👉Project wildrgbd.github.io/
👢"Virtual Try-All" by #Amazon 👢
👉#Amazon announces ”Diffuse to Choose”: diffusion-based image-conditioned inpainting for VTON. Virtually place any e-commerce item in any setting.
👉Review https://t.ly/at07Y
👉Paper https://lnkd.in/dxR7nGtd
👉Project diffuse2choose.github.io/
🫧 SAM + Open-Models 🫧
👉Grounded SAM (w/ DINO) as an open-set detector to combine with SAM. This integration enables the detection and segmentation of any regions based on arbitrary text inputs and opens a door to connecting various vision models. It can seamlessly integrate with other Open-World models to accomplish more intricate visual tasks.
👉Review https://t.ly/FwasQ
👉Paper https://arxiv.org/pdf/2401.14159.pdf
👉Code https://github.com/IDEA-Research/Grounded-Segment-Anything
🧪 SUPIR: SOTA restoration 🧪
👉SUPIR is the new SOTA in image restoration; suitable for restoration of blurry objects, defining the material texture of objects, and adjusting restoration based on high-level semantics
👉Review https://t.ly/wgObH
👉Project https://lnkd.in/dPcnBKWm
👉Paper https://lnkd.in/dZPYcUuq
👉Demo coming 🩷 but no code announced :(
🔥Lumiere: SOTA video-gen🔥
👉#Google unveils Lumiere: Space-Time Diffusion Model for Realistic Video Generation. It's the new SOTA, tasks: Text-to-Video, Video Stylization, Cinemagraphs & Video Inpainting.
👉Review https://t.ly/nalJR
👉Paper https://lnkd.in/d-PvrGjT
👉Project https://t.ly/gK8hz
🎭 UltrAvatar: ULTRA-Realistic Avatar 🎭
👉Novel 3D avatar with enhanced fidelity of geometry, and superior quality of physically based rendering (PBR) textures without unwanted lighting.
👉Review https://t.ly/B3BEu
👉Project https://lnkd.in/dkUQHFEV
👉Paper https://lnkd.in/dtEQxrBu
👉Code coming 🩷
