AI with Papers - Artificial Intelligence & Deep Learning

Открыть в Telegram

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

Малайзия2 241 Технологии и приложения7 723...

📈 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 17 147 подписчиков, занимая 7 723 место в категории Технологии и приложения и 2 241 место в регионе Малайзия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 17 147 подписчиков.

Согласно последним данным от 23 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -190, а за последние 24 часа — -2, при этом общий охват остаётся высоким.

Статус верификации: Не верифицирован
Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 25.09%. В первые 24 часа после публикации контент обычно набирает 6.86% реакций от общего числа подписчиков.
Охват публикаций: В среднем каждый пост получает 4 302 просмотров. В течение первых суток публикация набирает 1 177 просмотров.
Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 26.
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 24 июня, 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.

17 147

Подписчики

-224 часа

-367 дней

-19030 день

4 302

Просмотры поста

~ 1 17724 часа

~ 1 35348 часов

25.09%

Коэффициент вовлеченности

Нет данных

Постов в день

Ads index

beta

Архив постов

17 144

📫 MeshPose: DensePose + HMR 📫 👉MeshPose: novel approach to jointly tackle DensePose and Human Mesh Reconstruction in a while. A natural fit for #AR applications requiring real-time mobile inference. 👉Review https://t.ly/a-5uN 👉Paper https://arxiv.org/pdf/2406.10180 👉Project https://meshpose.github.io/

17 144

🎹 PianoMotion10M for gen-hands 🎹 👉PianoMotion10M: 116 hours of piano playing videos from a bird’s-eye view with 10M+ annotated hand poses. A big contributions in hand motion generation. Code & Dataset released💙 👉Review https://t.ly/_pKKz 👉Paper arxiv.org/pdf/2406.09326 👉Code https://lnkd.in/dcBP6nvm 👉Project https://lnkd.in/d_YqZk8x 👉Dataset https://lnkd.in/dUPyfNDA

17 144

🍉 MASA: MOT Anything By SAM 🍉 👉MASA: Matching Anything by Segmenting Anything pipeline to learn object-level associations from unlabeled images of any domain. An universal instance appearance model for matching any objects in any domain. Source code in June 💙 👉Review https://t.ly/pKdEV 👉Paper https://lnkd.in/dnjuT7xm 👉Project https://lnkd.in/dYbWzG4E 👉Code https://lnkd.in/dr5BJCXm

17 144

👑 Kling AI vs. OpenAI Sora 👑 👉Kling: the ultimate Chinese text-to-video model - rival to #OpenAI’s Sora. No papers or tech info to check, but stunning results from the official site. 👉Review https://t.ly/870DQ 👉Paper ??? 👉Project https://kling.kuaishou.com/

17 144

👗 SOTA Multi-Garment VTOn Editing 👗 👉#Google (+UWA) unveils M&M VTO, novel mix 'n' match virtual try-on that takes as input multiple garment images, text description for garment layout and an image of a person. It's the new SOTA both qualitatively and quantitatively. Impressive results! 👉Review https://t.ly/66mLN 👉Paper arxiv.org/pdf/2406.04542 👉Project https://mmvto.github.io

17 144

🧊 Universal 6D Pose/Tracking 🧊 👉Omni6DPose is a novel dataset for 6D Object Pose with 1.5M+ annotations. Extra: GenPose++, the novel SOTA in category-level 6D estimation/tracking thanks to two pivotal improvements. 👉Review https://t.ly/Ywgl1 👉Paper arxiv.org/pdf/2406.04316 👉Project https://lnkd.in/dHBvenhX 👉Lib https://lnkd.in/d8Yc-KFh

17 144

🚙 UA-Track: Uncertainty-Aware MOT🚙 👉UA-Track: novel Uncertainty-Aware 3D MOT framework which tackles the uncertainty problem from multiple aspects. Code announced, not released yet. 👉Review https://t.ly/RmVSV 👉Paper https://arxiv.org/pdf/2406.02147 👉Project https://liautoad.github.io/ua-track-website

17 144

📞FacET: VideoCall Change Your Expression📞 👉Columbia University unveils FacET: discovering behavioral differences between conversing face-to-face (F2F) and on video-calls (VCs). 👉Review https://t.ly/qsQmt 👉Paper arxiv.org/pdf/2406.00955 👉Project facet.cs.columbia.edu/ 👉Repo (empty) github.com/stellargo/facet

17 144

👹👹 AI and the Everything in the Whole Wide World Benchmark 👹👹 👉Last week Yann LeCun said something like "LLMs will not reach human intelligence". It's clear the on-going #deeplearning is not ready for "general AI", a "radical alternative" is necessary to create the “superintelligence”. 👉Review https://t.ly/isdxM 👉Paper https://lnkd.in/dFraieZS 👉News https://lnkd.in/da-7PnVT

17 144

👹👹👹👹 Last week Yann LeCun said something like "LLMs will not reach human intelligence". It's clear the on-going #deeplearning is not ready for "general AI", a "radical alternative" is necessary to create the “superintelligence”.

17 144

🐳 MultiPly: in-the-wild Multi-People 🐳 👉MultiPly: novel framework to reconstruct multiple people in 3D from monocular in-the-wild videos. It's the new SOTA over the publicly available datasets and in-the-wild videos. Source Code announced, coming💙 👉Review https://t.ly/_xjk_ 👉Paper arxiv.org/pdf/2406.01595 👉Project eth-ait.github.io/MultiPly 👉Repo github.com/eth-ait/MultiPly

17 144

🐳MultiPly: in-the-wild Multi-People from Mono🐳 👉MultiPly: novel framework to reconstruct multiple people in 3D from monocular in-the-wild videos. It's the new SOTA over the publicly available datasets and in-the-wild videos. Source Code announced, coming💙 #artificialintelligence #machinelearning #ml #AI #deeplearning #computervision #AIwithPapers #metaverse 👉Discussion https://lnkd.in/dMgakzWm 👉Paper https://arxiv.org/pdf/2406.01595 👉Project https://eth-ait.github.io/MultiPly/ 👉Repo https://github.com/eth-ait/MultiPly

17 144

🎭New 2D Landmarks SOTA🎭 👉Flawless AI unveils FaceLift, a novel semi-supervised approach that learns 3D landmarks by directly lifting (visible) hand-labeled 2D landmarks and ensures better definition alignment, with no need for 3D landmark datasets. No code announced🥹 👉Review https://t.ly/lew9a 👉Paper arxiv.org/pdf/2405.19646 👉Project davidcferman.github.io/FaceLift

17 144

🧤 Transformer-based 4D Hands 🧤 👉4DHands is a novel and robust approach to recovering interactive hand meshes and their relative movement from monocular inputs. Authors: Beijing Normal University, Tsinghua & #Lenovo. No code announced yet 😢 👉Review https://t.ly/wvG-l 👉Paper arxiv.org/pdf/2405.20330 👉Project 4dhands.github.io/

17 144

🪰 Dynamic Gaussian Fusion via 4D Motion Scaffolds 🪰 👉MoSca is a novel 4D Motion Scaffolds to reconstruct/synthesize novel views of dynamic scenes from monocular videos in the wild! 👉Review https://t.ly/nSdEL 👉Paper arxiv.org/pdf/2405.17421 👉Code github.com/JiahuiLei/MoSca 👉Project https://lnkd.in/dkjMVcqZ

17 144

🦓 Z.S. Diffusive Segmentation 🦓 👉KAUST (+MPI) announced the first zero-shot approach for Video Semantic Segmentation (VSS) based on pre-trained diffusion models. Source Code released under MIT💙 👉Review https://t.ly/v_64K 👉Paper arxiv.org/pdf/2405.16947 👉Project https://lnkd.in/dcSt4dQx 👉Code https://lnkd.in/dcZfM8F3

17 144

⛈️Unsupervised Neuromorphic Motion⛈️⛈️ 👉The Western Sydney University unveils a novel unsupervised event-based motion segmentation algorithm, employing the #Prophesee Gen4 HD event camera. 👉Review https://t.ly/UZzIZ 👉Paper https://arxiv.org/pdf/2405.15209 👉Project https://samiarja.github.io/evairborne/ 👉Repo (empty) https://github.com/samiarja/ev/_deep/_motion_segmentation

17 144

🔥 YOLOv10 Object Detector is out 🔥 👉YOLOv10: novel real-time end-to-end object detection. Code released under GNU GPL v3.0💙 👉Review https://shorturl.at/ZIHBh 👉Paper arxiv.org/pdf/2405.14458 👉Code https://github.com/THU-MIG/yolov10/

17 144

🍀 OmniGlue: Foundation Matcher 🍀 👉#Google OmniGlue from #CVPR24: the first learnable image matcher powered by foundation models. Impressive out-of-domain results! 👉Review https://t.ly/ezaIc 👉Paper https://arxiv.org/pdf/2405.12979 👉Project hwjiang1510.github.io/OmniGlue/ 👉Code https://github.com/google-research/omniglue/

17 144

👚 ViViD: Diffusion Virtual Try-ON 👚 👉ViViD is a novel framework employing powerful diffusion models to tackle the task of video virtual try-on. Code announced, not released yet😢 👉Review https://lnkd.in/dMgakzWm 👉Paper arxiv.org/pdf/2405.11794 👉Repo https://lnkd.in/dT4_bzPw 👉Project https://lnkd.in/dCK5ug4v