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7 721...

📈 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 17 206 名订阅者，在 技术与应用 类别中位列第 7 721，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 17 206 名订阅者。

根据 12 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 -128，过去 24 小时变化为 -1，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 19.19%。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 3 302 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 19。
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 13 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。

17 206

订阅者

-124 小时

-317 天

-12830 天

3 302

帖子浏览量

无数据24 小时

无数据48 小时

19.19%

参与率

无数据

每日帖子数

Ads index

beta

帖子存档

17 206

Hinton our guest in Pavia (remotely) 💚😈

17 206

🔥BoxerNet: SOTA 2D->3D BBs🔥 👉Boxer by #META: transformer-based network to lift 2D BB proposals into 3D, followed by multi-view fusion and geometric filtering to produce globally consistent de-duplicated 3DBBs in metric world space. Repo under A-NC 4.0 International💙 👉Review https://t.ly/mlmV1 👉Paper https://arxiv.org/pdf/2604.05212 👉Project facebookresearch.github.io/boxer/ 👉Repo github.com/facebookresearch/boxer

17 206

🔥Vanast: VTON w/ Human Animation🔥 👉SNU unveils a novel unified framework that generates garment-transferred human animation videos directly from a single human/garment images, and pose guidance clip. Repo announced💙 👉Review https://t.ly/c0t79 👉Paper arxiv.org/pdf/2604.04934 👉Project hyunsoocha.github.io/vanast/ 👉Repo github.com/snuvclab/vanast

17 206

🍎Video Object Deletion🍎 👉Void by Netflix is a novel video object removal framework designed to perform physically-plausible inpainting in very complex scenarios. Repo under Apache 2.0💙 👉Review https://t.ly/cMVny 👉Paper https://arxiv.org/pdf/2604.02296 👉Project https://void-model.github.io/ 👉Repo https://github.com/Netflix/void-model

17 206

If you have to invest TODAY 1B$ on a frontier tech for the next decade, would you invest in space, agentic, quantum or frugal GPUs? Vote here: https://t.ly/hSx6i

17 206

🪬Camera Raw Image Generation🪬 👉RawGen by #Samsung is a generative approach that learns the complex distribution of raw sensor data directly, enabling high-fidelity generation from either text descriptions or standard sRGB images across arbitrary camera sensors. Linear raw image once, then apply any ISP operation. Repo announced💙 👉Review https://t.ly/_QVKP 👉Paper https://arxiv.org/pdf/2604.00093 👉Project https://dy112.github.io/rawgen-page/ 👉Repo TBA

17 206

🌵SOTA Training-Free In-Context Segmentation🌵 👉INSID3 is the new SOTA, training-free approach that segments concepts at varying granularities only from frozen DINOv3 features, given an in-context example. Repo under Apache 2.0💙 👉Review https://t.ly/NVWHN 👉Paper https://arxiv.org/pdf/2603.28480 👉Project https://visinf.github.io/INSID3/ 👉Repo https://github.com/visinf/INSID3

17 206

👌HandX: Scaling Hands Motion👌 👉 HandX is a unified foundation spanning data, annotation, and evaluation: novel large-scale dataset of bimanual & dexterous motions with fine-grained textual. Around 6M frames. Repo available💙 👉Review https://t.ly/1nGxw 👉Paper https://arxiv.org/pdf/2603.28766 👉Project https://handx-project.github.io/ 👉Repo github.com/handx-project/HandX

17 206

💥 GaussianGPT 3D GSC💥 👉From TUM, GaussianGPT: transformer-based 3D Gaussians generation via next-token prediction -> full 3D complex indoor scene. Repo announced💙 👉Review https://t.ly/bj-lL 👉Paper https://arxiv.org/pdf/2603.26661 👉Project https://nicolasvonluetzow.github.io/GaussianGPT/ 👉Repo TBA

17 206

🐍Pose-Appearance-Motion for HOI🐍 👉PAM is a novel Pose–Appearance–Motion Engine for controllable Hand–Object Interaction SOTA video generation. Repo/models available💙 👉Review 👉Paper arxiv.org/pdf/2603.22193 👉Project gasaiyu.github.io/PAM.github.io/ 👉Repo https://github.com/GasaiYU/PAM

17 206

🦪OccAny: Universal 3D Occupancy🦪 👉OccAny by Valeo is a novel unified framework for generalized unconstrained urban 3D occupancy prediction. Repo under Apache 2.0💙 👉Review 👉Paper https://arxiv.org/pdf/2603.23502 👉Project https://valeoai.github.io/OccAny/ 👉Repo https://github.com/valeoai/OccAny

17 206

🍓Material-Aware Grouping🍓 👉Material Magic Wand (Adobe) is a tool for material-aware grouping of parts in untextured 3D meshes. Given one selected part, it automatically retrieves the other parts in the same shape by its material. Repo announced💙 👉Review https://t.ly/q00SU 👉Paper https://arxiv.org/pdf/2603.17370 👉Project umangi-jain.github.io/material-magic-wand/ 👉Repo TBA

17 206

🍧10,000× faster SAM-3D🍧 👉Fast SAM 3D Body achieves up to 10.9× speedup, over 10,000× faster MHR-to-SMPL conversion -> real-time humanoid control from RGB. Repo available💙 👉Review https://t.ly/uHx84 👉Paper https://arxiv.org/pdf/2603.15603 👉Project yangtiming.github.io/Fast-SAM-3D-Body-Page/ 👉Repo https://github.com/yangtiming/Fast-SAM-3D-Body

17 206

🤖Physically-Plausible Human🤖 👉PhysMoDPO is a novel direct preference optimization framework for humanoid motion generation. Repo under MIT💙 👉Review https://t.ly/clf8w 👉Paper https://arxiv.org/pdf/2603.13228 👉Project https://mael-zys.github.io/PhysMoDPO/ 👉Repo https://github.com/Mael-zys/PhysMoDPO

17 206

🌈 New SOTA Video Depth 🌈 👉DVD is the new Video Depth Estimation SOTA with full training suite available under Apache2.0💙 👉Review https://t.ly/gpCkG 👉Paper https://arxiv.org/pdf/2603.12250 👉Project https://dvd-project.github.io/ 👉Repo github.com/EnVision-Research/DVD

17 206

☄️OmniStream: Perceive-Reconstruct-Act ☄️ 👉Novel unified streaming visual backbone that effectively perceives, reconstructs, and acts from diverse visual inputs. Repo/Models announced💙 👉Review https://t.ly/_zZMO 👉Paper arxiv.org/pdf/2603.12265 👉Project go2heart.github.io/omnistream/ 👉Repo github.com/Go2Heart/OmniStream

17 206

🍓Surface Light Tokenizer🍓 👉Apple unveils LITO a novel latent flow matching model enables HQ image-to-3D. Latent representation that encodes a surface light field into a compact set of latent vectors. Impressive results but no code🥲 👉Review https://t.ly/xcWNe 👉Paper https://lnkd.in/dYHwY4YX 👉Project https://lnkd.in/dtJT8bXy

17 206

🔥Holistic 3D Spatial Intelligence🔥 👉Holi-Spatial is the first fully automated pipeline capable of converting raw video streams into holistic 3D spatial annotations without human intervention. Code/Data announced💙 👉Review https://t.ly/PDpr9 👉Paper https://lnkd.in/dTbMuZCm 👉Project https://lnkd.in/d66CYB4q 👉Repo https://lnkd.in/dAGzShXj

17 206

📊Real-Time Scene Graph📊 👉REACT++ by Umea University is the new state-of-the-art model for real-time SGG: 20% faster with a gain of 10% in relation prediction accuracy on average. Code under MIT💙 👉Review https://t.ly/c12VX 👉Paper https://arxiv.org/pdf/2603.06386 👉Repo https://github.com/Maelic/SGG-Benchmark

17 206

🎪SOTA Arbitrary Tracking🎪 👉TAPFormer is the novel SOTA transformer-based framework that performs asynchronous temporal-consistent fusion of frames and events for robust and high-freq point tracking. Repo & Dataset under MIT💙 👉Review https://t.ly/-q4wm 👉Paper https://arxiv.org/pdf/2603.04989 👉Project http://tapformer.github.io/ 👉Repo https://github.com/ljx1002/TAPFormer