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 17 166 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 17 166 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。

17 166

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

17 157

🔥 GAGA: Group Any Gaussians 🔥 👉GAGA is a framework that reconstructs and segments open-world 3D scenes by leveraging inconsistent 2D masks predicted by zero-shot segmentation models. Code available, recently updated💙 👉Review https://t.ly/Nk_jT 👉Paper www.gaga.gallery/static/pdf/Gaga.pdf 👉Project www.gaga.gallery/ 👉Repo github.com/weijielyu/Gaga

17 157

🧞‍♂️Omni-RGPT: SOTA MLLM Understanding🧞‍♂️ 👉 #NVIDIA presents Omni-RGPT, MLLM for region-level comprehension for both images & videos. New SOTA on image/video-based commonsense reasoning. 👉Review https://t.ly/KHnQ7 👉Paper arxiv.org/pdf/2501.08326 👉Project miranheo.github.io/omni-rgpt/ 👉Repo TBA soon

17 157

🆘 Help: Looking for Outstanding Speakers 🆘 👉Who would you suggest as a speaker for your ideal conference on AI (CV, LLM, RAG, ML, HW Optimization, AI & Space, etc.)? Only “hardcore” technical talks, no commercial at all. Please comment here with name, topic and affiliation (es: Paul Gascoigne, Computer Vision & Football, Scotland Team). ⭐Guaranteed tickets & more for the suggestions that will become invited speakers ;)

17 157

🏆Universal Detector-Free Match🏆 👉MatchAnything: novel detector-free universal matcher across unseen real-world single/cross-modality domains. Same weights for everything. Code announced, to be released 💙 👉Review https://t.ly/sx92L 👉Paper https://lnkd.in/dWwRwGyY 👉Project https://lnkd.in/dCwb2Yte 👉Repo https://lnkd.in/dnUXYzQ5

17 157

❤️‍🔥 Uncommon object in #3D ❤️‍🔥 👉#META releases uCO3D, a new object-centric dataset for 3D AI. The largest publicly-available collection of HD videos of objects with 3D annotations that ensures full-360◦ coverage. Code & data under CCA 4.0💙 👉Review https://t.ly/Z_tvA 👉Paper https://arxiv.org/pdf/2501.07574 👉Project https://uco3d.github.io/ 👉Repo github.com/facebookresearch/uco3d

17 157

🔥 Depth Any Camera (SOTA) 🔥 👉DAC is a novel and powerful zero-shot metric depth estimation framework that extends a perspective-trained model to effectively handle cams with varying FoVs (including large fisheye & 360◦). Code announced (not available yet)💙 👉Review https://t.ly/1qz4F 👉Paper arxiv.org/pdf/2501.02464 👉Project yuliangguo.github.io/depth-any-camera/ 👉Repo github.com/yuliangguo/depth_any_camera

17 157

⚽ FIFA 3D Human Pose ⚽ 👉#FIFA WorldPose is a novel dataset for multi-person global pose estimation in the wild, featuring footage from the 2022 World Cup. 2.5M+ annotation, released 💙 👉Review https://t.ly/kvGVQ 👉Paper arxiv.org/pdf/2501.02771 👉Project https://lnkd.in/d5hFWpY2 👉Dataset https://lnkd.in/dAphJ9WA

17 157

🔥 "Nuclear" AI vs. Hyper-Cheap Inference 🔥 ⭐ What do you expect in 2025 after the #Nvidia announcements at CES 2025? Free to comment :)

Anonymous voting

17 157

🧤World-Space Ego 3D Hands🧤 👉The Imperial College unveils HaWoR, a novel world-space 3D hand motion estimation for egocentric videos. The new SOTA on both cam pose estimation & hand motion reconstruction. Code under Attribution-NC-ND 4.0 Int.💙 👉Review https://t.ly/ozJn7 👉Paper arxiv.org/pdf/2501.02973 👉Project hawor-project.github.io/ 👉Code github.com/ThunderVVV/HaWoR

17 157

🥮 SOTA probabilistic tracking🥮 👉ProTracker is a novel framework for robust and accurate long-term dense tracking of arbitrary points in videos. Code released under CC Attribution-NonCommercial💙 👉Review https://t.ly/YY_PH 👉Paper https://arxiv.org/pdf/2501.03220 👉Project michaelszj.github.io/protracker/ 👉Code github.com/Michaelszj/pro-tracker

17 157

What is your favorite source for the AI updates?

Anonymous voting

17 157

⭐ Poll Alert!! ⭐ [EDIT] see below

17 157

⭐ Quick poll to start 2025 ⭐ What is your favorite source for the AI updates? Please vote here: https://t.ly/chQWq Thanks!

17 157

🌳 HD Video Object Insertion 🌳 👉VideoAnydoor is a novel zero-shot video object insertion #AI with high-fidelity detail preservation and precise motion control. All-in-one: video VTON, face swapping, logo insertion, multi-region editing, etc. 👉Review https://t.ly/hyvRq 👉Paper arxiv.org/pdf/2501.01427 👉Project videoanydoor.github.io/ 👉Repo TBA

17 157

⭐TOP 10 Papers you loved - 2024⭐ 👉Here the list of my posts you liked the most in 2024, thank you all 💙 𝐏𝐚𝐩𝐞𝐫𝐬: ⭐"Look Ma, no markers" ⭐T-Rex 2 Detector ⭐Models at Any Resolution 👉The full list with links: https://t.ly/GvQVy

17 157

🔄️ Orient Anything in 3D 🔄️ ️ 👉Orient Anything is a novel robust image-based object orientation estimation model. By training on 2M rendered labeled images, it achieves strong zero-shot generalization in the wild. Code released💙 👉Review https://t.ly/ro5ep 👉Paper arxiv.org/pdf/2412.18605 👉Project orient-anything.github.io/ 👉Code https://lnkd.in/d_3k6Nxz

17 157

🍄 Open-MLLMs Self-Driving 🍄 👉OpenEMMA: a novel open-source e2e framework based on MLLMs (via Chain-of-Thought reasoning). Effectiveness, generalizability, and robustness across a variety of challenging driving scenarios. Code released under Apache 2.0💙 👉Review https://t.ly/waLZI 👉Paper https://arxiv.org/pdf/2412.15208 👉Code https://github.com/taco-group/OpenEMMA

17 157

🫶 Dynamic Cam-4D Hands 🫶 👉The Imperial College unveils Dyn-HaMR, the first approach to reconstruct 4D global hand motion from monocular videos recorded by dynamic cameras in the wild. Code announced under MIT💙 👉Review https://t.ly/h5vV7 👉Paper arxiv.org/pdf/2412.12861 👉Project dyn-hamr.github.io/ 👉Repo github.com/ZhengdiYu/Dyn-HaMR

17 157

🐕 Gaze-LLE: Neural Gaze 🐕 👉Gaze-LLE: novel transformer framework that streamlines gaze target by leveraging features from frozen DINOv2 encoder. Code & models under MIT 💙 👉Review https://t.ly/SadoF 👉Paper arxiv.org/pdf/2412.09586 👉Repo github.com/fkryan/gazelle

17 157

🌹 4D Neural Templates 🌹 👉#Stanford unveils Neural Templates, generating HQ temporal object intrinsics for several natural phenomena and enable the sampling and controllable rendering of these dynamic objects from any viewpoint, at any time of their lifespan. A novel task in vision is born💙 👉Review https://t.ly/ka_Qf 👉Paper https://arxiv.org/pdf/2412.05278 👉Project https://chen-geng.com/rose4d#toi