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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Малайзия2 234 Технологии и приложения7 718...

📈 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 17 166 подписчиков, занимая 7 718 место в категории Технологии и приложения и 2 234 место в регионе Малайзия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 17 166 подписчиков.

Согласно последним данным от 20 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -169, а за последние 24 часа — 0, при этом общий охват остаётся высоким.

Статус верификации: Не верифицирован
Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 22.86%. В первые 24 часа после публикации контент обычно набирает N/A% реакций от общего числа подписчиков.
Охват публикаций: В среднем каждый пост получает 3 926 просмотров. В течение первых суток публикация набирает 0 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 21 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.

17 166

Подписчики

Нет данных24 часа

-357 дней

-16930 день

3 926

Просмотры поста

Нет данных24 часа

Нет данных48 часов

22.86%

Коэффициент вовлеченности

Нет данных

Постов в день

Ads index

beta

Архив постов

17 166

💃 Video Motion Graphs 💃 👉#Adobe unveils a novel system designed to generate realistic human motion videos. Using a reference video and conditional signals such as music or motion tags, the system synthesizes amazing new videos. Code & Models to be released💙 👉Review https://t.ly/r4EGF 👉Paper https://lnkd.in/dK_tHyzh 👉Project https://lnkd.in/dE6c_KYZ 👉Repo TBA

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🐟Segment Any Motion in Video🐟 👉From CVPR2025 a novel approach for moving object segmentation that combines DINO-based semantic features and SAM2. Code under MIT license💙 👉Review https://t.ly/4aYjJ 👉Paper arxiv.org/pdf/2503.22268 👉Project motion-seg.github.io/ 👉Repo github.com/nnanhuang/SegAnyMo

17 166

🌳MSVA Zero-Shot Multi-View🌳 👉Niantic unveils MVSA, novel Multi-View Stereo Architecture to work anywhere by generalizing across diverse domains & depth ranges. Highly accurate & 3D-consistent depths. Code & models announced💙 👉Review https://t.ly/LvuTh 👉Paper https://arxiv.org/pdf/2503.22430 👉Project https://nianticlabs.github.io/mvsanywhere/ 👉Repo https://lnkd.in/ddQz9eps

17 166

🏓LATTE-MV: #3D Table Tennis🏓 👉UC Berkeley unveils at #CVPR2025 a novel system for reconstructing monocular video of table tennis in 3D with uncertainty-aware controller that anticipates opponent actions. Code & Dataset announced, to be released💙 👉Review https://t.ly/qPMOU 👉Paper arxiv.org/pdf/2503.20936 👉Project sastry-group.github.io/LATTE-MV/ 👉Repo github.com/sastry-group/LATTE-MV

17 166

🦎 Scaling Vision to 4K🦎 👉PS3 by #Nvidia (+UC Berkeley) to scale-up CLIP-style vision pre-training to 4K with *near-constant* cost. Encoding LR global image and selectively processes only informative HR regions. Impressive work. Code/weights & 🤗 announced💙 👉Review https://t.ly/WN479 👉Paper https://lnkd.in/ddWq8UpX 👉Project https://lnkd.in/dMkTY8-k 👉Repo https://lnkd.in/d9YSB6yv

17 166

🔥 Dereflection Any Image 🔥 👉SJTU & #Huawei unveils DAI, novel diffusion-based framework able to recover from a wide range of reflection types. One-step diffusion with deterministic outputs & fast inference. Inference, pretrained models & training released💙 👉Review https://t.ly/PDA9K 👉Paper https://arxiv.org/pdf/2503.17347 👉Project abuuu122.github.io/DAI.github.io/ 👉Repo github.com/Abuuu122/Dereflection-Any-Image

17 166

🙀3D MultiModal Memory🙀 👉M3 is a novel framework by UCSD & #NVIDIA for rendering 3D scenes w/ RGB & foundation model embeddings. Rich spatial & semantic understanding via novel memory system designed to retain multimodal info through videos 👉Review https://t.ly/OrXZO 👉Paper arxiv.org/pdf/2503.16413 👉Project https://lnkd.in/dXAZ97KH 👉Repo https://lnkd.in/dWvunCET

17 166

🥎LLM Spatial Understanding🥎 👉SpatialLM by Manycore: novel LLM designed to process 3D point cloud data and generate structured 3D scene understanding outputs. Code, model & data 💙 👉Review https://t.ly/ejr1s 👉Project manycore-research.github.io/SpatialLM/ 👉Code github.com/manycore-research/SpatialLM 🤗Models https://huggingface.co/manycore-research

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teaser (1) (online-video-cutter.com) (1).mp42.02 MB

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🧞 IMPOSSIBLE Videos 🧞 👉IPV-Bench: counterfactual and anti-reality scenes impossible in real world. A novel challenge designed to evaluate and foster progress in video understanding and generation. Code & 🤗-Data 💙 👉Review https://t.ly/D7jhm 👉Paper arxiv.org/pdf/2503.14378 👉Project showlab.github.io/Impossible-Videos/ 👉Repo github.com/showlab/Impossible-Videos

17 166

🌱 #Py4AI: line-up is official 🌱 👉Last week we announced the first part of our incredible line-up for PY4AI 2025. It's time to disclose the second one and drive you crazy👇 𝐓𝐡𝐞 𝐬𝐞𝐜𝐨𝐧𝐝 𝐛𝐚𝐭𝐜𝐡 𝐨𝐟 𝐬𝐩𝐞𝐚𝐤𝐞𝐫𝐬: 🔥Alfredo Canziani | New York University 🔥Fanny Bouton | OVHcloud 🔥Full list: https://t.ly/JJP8B

17 166

🧸 Occluded 3D Reconstruction 🧸 👉Oxford unveils a novel 3D generative model to reconstruct 3D objects from partial observations. Code (TBR), demo, model on HF💙 👉Review https://t.ly/Lr5D7 👉Paper arxiv.org/pdf/2503.13439 👉Project sm0kywu.github.io/Amodal3R/ 🤗huggingface.co/spaces/Sm0kyWu/Amodal3R

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🖲️ VGG Transformer 🖲️ 👉VGGT by VGG & #META (#CVPR2025) is a feed-forward neural net. that directly infers all key 3D attributes of a scene within seconds. Code released💙 👉Review https://t.ly/WoWXL 👉Paper https://arxiv.org/pdf/2503.11651 👉Project https://vgg-t.github.io/ 👉Code github.com/facebookresearch/vggthttps://t.ly/WoWXL

17 166

🍾 6D Tracking & Pose SOTA 🍾 👉ČVUT unveils the new SOTA in RGB 6D pose estimation and tracking. Suitable for ego-clips & 7-axis robo-manipulation. Code under MIT💙 👉Review https://t.ly/pSqFR 👉Paper arxiv.org/pdf/2503.10307 👉Code github.com/ponimatkin/freepose

17 166

🫀HyperFast Mycardium tracking🫀 👉Norwegian institutes unveil MyoTracker, a low-complexity architecture (0.3M params) for point tracking in echocardiography. Built on CoTracker2, it provides point predictions for the entire sequence in a single step. Code released under non commercial license💙 👉Review https://t.ly/6wo8q 👉Paper https://arxiv.org/pdf/2503.10431 👉Code https://github.com/artemcher/myotracker

17 166

🐶OVTR: E2E Transformer MOT🐶 👉HUST University proposes OVTR (End-to-End Open-Vocabulary Multiple Object Tracking with TRansformer), the first end-to-end open-vocabulary tracker that models motion, appearance, and category simultaneously. Source Code released under MIT💙 👉Review https://t.ly/K3ASX 👉Paper arxiv.org/pdf/2503.10616 👉Code https://github.com/jinyanglii/OVTR

17 166

🎯RexSeek: Referring Any Object🎯 👉Novel referring detection model based on multimodal LLM to precisely locate objects based on user-input natural language. Model specialization on humans. Code released 💙 👉Review https://shorturl.at/CGsT2 👉Paper arxiv.org/pdf/2503.08507 👉Code github.com/IDEA-Research/RexSeek

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💙 Announcing #Py4AI 2025 💙 👉 The second edition of Py4AI conference is official! An all-day, fully free, event for #AI & #Python lovers. 𝐓𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐛𝐚𝐭𝐜𝐡 𝐨𝐟 𝐬𝐩𝐞𝐚𝐤𝐞𝐫𝐬: 🚀Dana Aubakirova | Hugging Face🤗 🚀Yunhao Liu & Ruoya Sheng | ByteDance🔥 🚀Alice Casiraghi | 🌏🌎🌍 🚀Luca Arrotta, PhD | Datapizza🍕 🚀Valeria Zuccoli | Bettini Srl 🚀Mirco Planamente | ARGO Vision 🚀Daniele Zonca | Red Hat 👉 Info & registration: https://t.ly/37wWj

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📒 Moving-Camera Diffusion 📒 👉Tencent unveils TrajectoryCrafter, a novel approach to redirect camera trajectories for monocular videos. Impressive results, the future of commercial #adv. Code & Demo released💙 👉Review https://t.ly/L-IoR 👉Paper https://arxiv.org/pdf/2503.05638 👉Project https://trajectorycrafter.github.io/ 👉Repo github.com/TrajectoryCrafter/TrajectoryCrafter 🤗Demo https://huggingface.co/spaces/Doubiiu/TrajectoryCrafter