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

17 166

💃 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

17 166

🐟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

17 166

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

17 166

🧞 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

17 166

🖲️ 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

17 166

💙 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

17 166

📒 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