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

🛸Real-Time Differentiable Tracing🛸 👉 Radiant Foam is a novel scene representation by leveraging the decades-old efficient volumetric mesh ray tracing algorithm (largely overlooked in recent research). Performing like Gaussian Splatting, without the constraints of rasterization. Code announced💙 👉Review https://shorturl.at/26U06 👉Paper https://arxiv.org/pdf/2502.01157 👉Project https://radfoam.github.io/ 👉Repo https://github.com/theialab/radfoam

17 157

🐙MambaGlue: SOTA feats. matching🐙 👉MambaGlue is a hybrid neural network combining the Mamba and the Transformer architectures to match local features. Source Code announced, to be released💙 👉Review https://shorturl.at/LxDG1 👉Paper arxiv.org/pdf/2502.00462 👉Repo https://lnkd.in/dAujfGZQ

17 157

🈯 SOTA 0-Shot Multi-View 🈯 👉MVGD by #TOYOTA is the SOTA method that generates images and scale-consistent depth maps from novel viewpoints given an arbitrary number of posed input views. A novel diffusion-based architecture capable of direct pixel-level generation. Code announced 💙 👉Review https://t.ly/_ecKl 👉Paper arxiv.org/pdf/2501.18804 👉Project mvgd.github.io/ 👉Repo TBA

17 157

💎AI-driven Docs Conversion💎 👉Docling by IBM, is the ALL-in-ONE, open source solution for documents; parsing several types of popular formats into a unified, richly structured representation. Powered by SOTA models for layout (DocLayNet) and table structure (TableFormer), it runs efficiently on low-cost hardware. Code under MIT💙 👉Review https://t.ly/nSCfT 👉Paper https://lnkd.in/dc5Kpc2F 👉Repo https://lnkd.in/d9gvw9bt

17 157

Social feed of everyone is broken because of unnecessary/not required opinions about DeepSeek. Your wish:

Anonymous voting

17 157

🌅 Generative Human Mesh Recovery 🌅 👉GenHMR is a novel generative framework that reformulates monocular HMR as an image-conditioned generative task, explicitly modeling and mitigating uncertainties in 2D-to-3D mapping process. Impressive results but no code announced 🥺 👉Review https://t.ly/Rrzpj 👉Paper https://arxiv.org/pdf/2412.14444 👉Project m-usamasaleem.github.io/publication/GenHMR/GenHMR.html

17 157

☀️ Relightable Full-Body Avatars ☀️ 👉#Meta unveils the first approach ever to jointly model the relightable appearance of the body, face, and hands of drivable avatars. 👉Review https://t.ly/kx9gf 👉Paper arxiv.org/pdf/2501.14726 👉Project neuralbodies.github.io/RFGCA

17 157

🦕[SOTA] Visual Grounding VOS🦕 👉ReferDINO is the first end-to-end approach for adapting foundational visual grounding models to RVOS. Code & models to be released soon💙 👉Review https://t.ly/SDFy9 👉Paper arxiv.org/pdf/2501.14607 👉Project isee-laboratory.github.io/ReferDINO/ 👉Repo github.com/iSEE-Laboratory/ReferDINO

17 157

🎨MatAnyone: Human Matting🎨 👉MatAnyone is a novel approach for human video matting that supports the target assignment. Stable tracking in long videos even with complex/ambiguous BGs. Code & 🤗-Demo announced💙 👉Review https://t.ly/NVXsT 👉Paper arxiv.org/pdf/2501.14677 👉Project pq-yang.github.io/projects/MatAnyone 👉Repo TBA

17 157

🪆SOTA Points Segmentation🪆 👉VGG Oxford unveils a novel loss to segment objects in videos based on their motion and NO other forms of supervision! Training the net using long-term point trajectories as a supervisory signal to complement optical flow. New SOTA! 👉Review https://t.ly/8Bsbt 👉Paper https://arxiv.org/pdf/2501.12392 👉Code https://github.com/karazijal/lrtl 👉Project www.robots.ox.ac.uk/~vgg/research/lrtl/

17 157

🔥 The code of DynOMo is out 🔥 👉DynOMo is a novel model able to track any point in a dynamic scene over time through 3D reconstruction from monocular video: 2D and 3D point tracking from unposed monocular camera input 👉Review https://t.ly/t5pCf 👉Paper https://lnkd.in/dwhzz4_t 👉Repo github.com/dvl-tum/DynOMo 👉Project https://lnkd.in/dMyku2HW

17 157

🔥 The code of DynOMo is out 🔥 👉DynOMo is a novel model able to track any point in a dynamic scene over time through 3D reconstruction from monocular video: 2D and 3D point tracking from unposed monocular camera input. Source code released under BSD 3-Clause💙 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅TUM, CMU (H/T Jenny Seidenschwarz) & NVIDIA ✅Online 2D/3D point tracking from unposed monocular ✅Tracking-by-reconstruction baseline for online TAP ✅New baseline for online PT with unposed mono-cam hashtag#artificialintelligence hashtag#machinelearning hashtag#ml hashtag#AI hashtag#deeplearning hashtag#computervision hashtag#AIwithPapers hashtag#metaverse hashtag#LLM 👉Discussion https://lnkd.in/dMgakzWm 👉Paper https://lnkd.in/dwhzz4_t 👉Repo github.com/dvl-tum/DynOMo 👉Project https://lnkd.in/dMyku2HW

17 157

🦠A-Life with Foundation Models🦠 👉A super team unveils ASAL, a new paradigm for Artificial Life research. A diverse range of ALife substrates including Boids, Particle Life, Game of Life, Lenia & Neural Cellular Automata. Code under Apache 2.0💙 👉Review https://t.ly/7SZ8A 👉Paper arxiv.org/pdf/2412.17799 👉Project http://pub.sakana.ai/asal/ 👉Repo https://lnkd.in/dP5yxKtw

17 157

🎤EMO2: Audio-Driven Avatar🎤 👉Alibaba previews a novel audio-driven talking head method capable of simultaneously generating highly expressive facial expressions and hand gestures. Turn your audio ON. Stunning results but no code 🥺 👉Review https://t.ly/x8slQ 👉Paper arxiv.org/pdf/2501.10687 👉Project humanaigc.github.io/emote-portrait-alive-2/ 👉Repo 🥺

17 157

🧵Time-Aware Pts-Tracking🧵 👉Chrono: feature backbone specifically designed for point tracking with built-in temporal awareness. Long-term temporal context, enabling precise prediction even without the refinements. Code announced💙 👉Review https://t.ly/XAL7G 👉Paper arxiv.orgzpdf/2501.12218 👉Project cvlab-kaist.github.io/Chrono/ 👉Repo github.com/cvlab-kaist/Chrono

17 157

🔥 [SOTA] Long-Video Depth Anything 🔥 👉ByteDance unveils Video Depth Anything: HQ, consistent depth estimation in SUPER-long videos (over several minutes) without sacrificing efficiency. Based on Depth Anything V2 with a novel efficient spatial-temporal head. Repo available under Apache 2.0💙 👉Review https://t.ly/Q4ZZd 👉Paper arxiv.org/pdf/2501.12375 👉Project https://lnkd.in/dKNwJzbM 👉Repo https://lnkd.in/ddfwwpCj

17 157

🌈 #Nvidia Foundation ZS-Stereo 🌈 👉Nvidia unveils FoundationStereo, a foundation model for stereo depth estimation with strong zero-shot generalization. In addition, a large-scale (1M stereo pairs) synthetic training dataset featuring large diversity and high photorealism. Code, model & dataset to be released💙 👉Review https://t.ly/rfBr5 👉Paper arxiv.org/pdf/2501.09898 👉Project nvlabs.github.io/FoundationStereo/ 👉Repo github.com/NVlabs/FoundationStereo/tree/master

17 157

🧽 Diffusion Video Inpainting 🧽 👉#Alibaba unveils a technical report about DiffuEraser, a video inpainting model based on stable diffusion, designed to fill masked regions with greater details and more coherent structures. Code & weights released under Apache💙 👉Review https://t.ly/7rEll 👉Paper arxiv.org/pdf/2501.10018 👉Project lixiaowen-xw.github.io/DiffuEraser-page/ 👉Repo github.com/lixiaowen-xw/DiffuEraser

17 157

🏄‍♀️ GSTAR: Gaussian Surface Tracking 🏄‍♀️ 👉ETH Zurich unveils GSTAR, a novel framework for photo-realistic rendering, surface reconstruction, and 3D tracking for dynamic scenes while handling topology changes. Code announced💙 👉Review https://t.ly/udpMq 👉Paper arxiv.org/pdf/2501.10283 👉Project chengwei-zheng.github.io/GSTAR/ 👉Repo TBA

17 157

🎁Free Book: LLM Foundations🎁 👉A fully free book just released on arXiv to outline the basic concepts of #LLMs and related techniques with a focus on the foundational aspects. ✅Chapter 1: basics of pre-training ✅Chapter 2: gen-models & LLMs ✅Chapter 3: prompting methods ✅Chapter 4: alignment methods 👉If you have any background in ML, along with a certain understanding of stuff like Transformers, this book will be "smooth". However, even without this prior knowledge, it is still perfectly fine because the contents of each chapter are self-contained. 👉Review https://t.ly/9LGCa 👉Book https://lnkd.in/d3VkswZf