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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马来西亚2 234 技术与应用7 718...

📈 Telegram 频道 AI with Papers - Artificial Intelligence & Deep Learning 的分析概览

频道 AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) 英语语言赛道中的是活跃参与者。目前社区聚集了 17 168 名订阅者，在 技术与应用 类别中位列第 7 718，并在 马来西亚 地区排名第 2 234 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 17 168 名订阅者。

根据 20 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 -169，过去 24 小时变化为 0，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 22.86%。内容发布后 24 小时内通常能获得 N/A% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 3 926 次浏览，首日通常累积 0 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 26。
主题关注点： 内容集中在 framework, object, dataset, tba, depth 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“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”

凭借高频更新（最新数据采集于 21 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。

17 168

订阅者

无数据24 小时

-357 天

-16930 天

3 926

帖子浏览量

无数据24 小时

无数据48 小时

22.86%

参与率

无数据

每日帖子数

Ads index

beta

帖子存档

17 166

⚽SoccerNet 2025 results are out!⚽ 👉SoccerNet 2025 Challenges is the open benchmarking dedicated to advancing computer vision research in football video understanding. Repo for training & Dataset💙 👉Review https://t.ly/MfHKg 👉Paper https://arxiv.org/pdf/2508.19182 👉Project https://www.soccer-net.org/ 👉Repo https://github.com/SoccerNet

17 166

🥶 OmniHuman-1.5 🥶 👉#ByteDance proposes a novel framework designed to generate character animations that are not only physically plausible but also semantically coherent and expressive. Coherency with speech's rhythm, prosody and semantic content. Impressive results but no code 🥺 👉Review https://t.ly/CnRmX 👉Paper arxiv.org/pdf/2508.19209 👉Project omnihuman-lab.github.io/v1_5/ 👉Repo 🥺

17 166

🏎️ VROOM: F1 Reconstruction🏎️ 👉Berkeley unveils VROOM, the first attempt for reconstructing 3D models of #Formula1 circuits using only onboard camera footage from racecars. Extreme challenges due to noise & speed. Repo released💙 👉Review https://t.ly/uuHdT 👉Paper arxiv.org/pdf/2508.17172 👉Repo github.com/yajatyadav/vroom 👉Project varun-bharadwaj.github.io/vroom/

17 166

🧤Diffusive Hand from Signs🧤 👉LIGM + #NVIDIA unveil a novel generative model of 3D hand motions from Sign Language Data. Motion characteristics such as handshapes, locations, finger, hand & arm movements. Code, Models & Data to be released 💙 👉Review https://t.ly/HonX_ 👉Paper https://arxiv.org/pdf/2508.15902 👉Project https://imagine.enpc.fr/~leore.bensabath/HandMDM/ 👉Data drive.google.com/drive/u/1/folders/1BLsu2hAqhAJ_gnGb9TNXW7MLiSuSEzEj 👉Repo TBA

17 166

🫔ATLAS: SOTA Human Model🫔 👉#META presents ATLAS, a novel high-fidelity body model learned from 600k high-res. scans captured using 240 synchronized cams. Code announced, to be released💙 👉Review https://t.ly/0hHud 👉Paper https://arxiv.org/pdf/2508.15767 👉Project https://jindapark.github.io/projects/atlas/ 👉Repo TBA

17 166

🔬Intern-S1: SOTA MM-MoE 🔬 👉InternS1: a MM-MoE with 28B activated / 241b total parameters, continually pre-trained on 5T tokens, including 2.5T+ tokens from scientific domains. New SOTA for professional tasks, such as molecular synthesis planning, reaction condition prediction, etc. Models available under Apache 2.0💙 👉Review https://t.ly/3l5UW 👉Paper arxiv.org/pdf/2508.15763 👉Repo github.com/InternLM/Intern-S1 🤗HF huggingface.co/internlm/Intern-S1

17 166

🧉 YOPO: SOTA 9-DoF Pose🧉 👉Pit In Co. unveils YOPO, a novel single-stage, query-based framework that treats category-level 9-DoF estimation as a natural extension of 2D detection. A practical solution for mono-RGB, category-level, multi-obj pose estimation. Code & models announced (coming)💙 👉Review https://t.ly/cf_Cl 👉Paper https://arxiv.org/pdf/2508.14965 👉Project mikigom.github.io/YOPO-project-page/ 👉Repo TBA

17 166

📡 ROVR Open Dataset is out 📡 👉A novel large-scale open 3D dataset for autonomous driving, robotics, and 4D perception tasks. To be released for academic (for free) & commercial💙 👉Review https://t.ly/iDcvg 👉Paper https://arxiv.org/pdf/2508.13977 👉Project https://xiandaguo.net/ROVR-Open-Dataset

17 166

👠 OmniTry: Virtual Try-On Anything 👠 👉OmniTry: unified framework that extends VTON beyond garment to encompass any wearable objects (jewelries, accessories, etc.) in mask-free setting. Weights, HF demo & benchmark released💙 👉Review https://t.ly/wMBGQ 👉Paper https://lnkd.in/dQe9MchS 👉Project https://omnitry.github.io/ 👉Repo https://lnkd.in/d3QwAXY2 🤗Demo https://lnkd.in/duUcZpVA

17 166

🌈DAViD: Synthetic Depth-Normal-Segmentation🌈 👉#Microsoft unveils DAViD: 100% synthetic dataset/models for human Depth, Normals & Segmentation. Impressive results at a fraction of the cost of the foundation models! Compliancy with privacy, copyright, licensing, and diversity requirements. Dataset available, models & runtime under MIT💙 👉Review https://t.ly/-SlO_ 👉Paper https://lnkd.in/eCmMXpTg 👉Project https://lnkd.in/eurCSWkm 👉Repo https://lnkd.in/e7PWFgP2

17 166

🔀4DNeX: Feed-Forward 4D video🔀 👉4DNeX is the first feed-forward framework for generating 4D scene representations from a single image by fine-tuning diffusion model. HQ dynamic pt-clouds & downstream tasks such as novel-view video synthesis with strong generalizability. Code/Data announced 💙 👉Review https://t.ly/SpkD- 👉Paper arxiv.org/pdf/2508.13154 👉Project https://4dnex.github.io/ 👉Repo github.com/3DTopia/4DNeX 👉Data https://lnkd.in/dh4_3Ghf 👉Demo https://lnkd.in/dztyzwgg

17 166

🏓TOTNet: Occlusion-aware Tracking🏓 👉TOTNet is a novel Temporal Occlusion Tracking Network that leverages 3D-convs, visibility-weighted loss, & occlusion augmentation to improve performance under occlusions. Code & Data available under MIT💙 👉Review https://t.ly/Q0jAf 👉Paper https://lnkd.in/dUYsa-GC 👉Repo https://lnkd.in/d3QGUHYb

17 166

🤖 Impact of SuperHuman AI 🤖 👉The NoProfit AI Futures Project unveils a (dystopic) scenario about what super-AI might look like. Forecast from today to the bio-engineered human-like creatures. A fascinating speculation of the future with the "slow-down" and "race" scenarios. Enjoy 💙 👉Review https://t.ly/EgmfJ 👉Project https://ai-2027.com/

17 166

🦖 #META's DINOv3 is out 🦖 👉#Meta unveils DINOv3! A novel foundation model outperforming the previous SOTAs in computer vision. Code & weights released under DINOv3 License💙 👉Review https://t.ly/-S3ZL 👉Paper https://t.ly/ervOT 👉Project https://lnkd.in/dHFf3esd 👉Repo https://lnkd.in/dPxhDxAq 🤗HF https://lnkd.in/dWGudY2i

17 166

Hi everybody, I took a few weeks to take a breath from a lot of stuff, I dedicated all my mental energy to keep working and I dedicated all my spare time to take care of myself. Despite I'm still not ok (BTW, my health was/is always good), I feel it's time to come back and support this wonderful community in this journey. I feel the responsibility of that, time to get in the ring. I'm very sorry for being out so long, but sometime life hits really hard. I got an incredible support from unknown people from all around the world. It's amazing. Thanks again, you rock! Alessandro.

17 166

Dear friends, I’m truly sorry for being away from the group for so long. I know: no updates so far while AI is running faster than speed of light. I’m going through a very difficult time in my life and I need some space to heal. This spare-time project (but important for a lot of people here) needs energy and commitment I don’t have right now. I’m sorry, be patient. I’ll be back. Love u all, Alessandro.

17 166

🧞‍♀️GENMO: Generalist Human Motion 🧞‍♀️ 👉#Nvidia presents GENMO, a unified Generalist Model for Human Motion that bridges motion estimation and generation in a single framework. Conditioning on videos, 2D keypoints, text, music, and 3D keyframes. No code at the moment🥲 👉Review https://t.ly/Q5T_Y 👉Paper https://lnkd.in/ds36BY49 👉Project https://lnkd.in/dAYHhuFU

17 166

🩷Dance vs. #ComputerVision🩷 👉The Saint-Etienne university proposed a new 3D human body pose estimation pipeline to deal with dance analysis. Project page w/ results and interactive demo released💙 👉Review https://t.ly/JEdM3 👉Paper arxiv.org/pdf/2505.07249 👉Project https://lnkd.in/dD5dsMv5