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

17 168

🦗Character Mixing Generation🦗 👉MBZUAI unveils the first ever video-gen system able to preserve character ID, behavior & original style while generating plausible interactions between characters that have never coexisted - from cartoons (We Bare Bears, Tom & Jerry) to realistic humans (Mr. Bean, Young Sheldon) 👉Review https://t.ly/tN84a 👉Paper https://lnkd.in/dhKMwukv 👉Project https://lnkd.in/dBkJs48h 👉Repo https://lnkd.in/dw_uzgAk

17 168

🐠ITTO: Protocol for Dynamic Tracking🐠 👉ITTO by Caltech is a novel long-range tracking benchmark suite for evaluating and diagnosing tracking methods on complex and long-range motions. Repo under CC BY-NC 4.0💙 👉Review https://t.ly/tN84a 👉Paper https://arxiv.org/pdf/2510.19819 👉Project https://glab-caltech.github.io/ITTO/ 👉Repo https://github.com/ilonadem/itto

17 168

🏜️Omni Driving Navigation Models🏜️ 👉OmniNWM is a unified panoramic navigation world model that advances autonomous driving by jointly generating multi-modal states (RGB, semantics, depth, 3D occupancy), enabling precise action control & facilitating closed-loop evaluation through occupancy-based dense rewards. Repo under Apache 2.0💙 👉Review https://t.ly/ktXvz 👉Paper https://lnkd.in/eFKSZnrc 👉Project https://lnkd.in/eSDfccv8 👉Repo https://lnkd.in/efCSvjtp

17 168

Repo (pretty empty) now online: https://github.com/OatmealLiu/UrbanVerse

17 168

🔥 SAM 2++: Track Anything 🔥 👉SAM 2++ is a novel unified model towards tracking at any granularity, including masks, boxes, and points. Impressive results but no code announced yet 😢 👉Review https://t.ly/I392_ 👉Paper arxiv.org/pdf/2510.18822 👉Project tracking-any-granularity.github.io/ 👉Repo :(

17 168

🌵All-in-One Dense Keypoints🌵 👉DeepDetect is a novel all-in-one, dense keypoints detector that unifies the strengths of SIFT, ORB, BRISK, FAST, AGAST, Harris, Shi-Tomasi, Canny & Sobel into a neural net. DAMN ROMANTIC. Repo under MIT💙 👉Review https://t.ly/VKGct 👉Paper https://arxiv.org/pdf/2510.17422 👉Repo https://github.com/saktx/DeepDetect

17 168

🦄 City-Tour -> Simulation 🦄 👉UrbanVerse is a novel system to convert real-world urban scenes from city-tour videos into physics-aware, interactive simulation environments, enabling scalable robot learning in urban spaces with real-world generalization. Repo & Data announced 💙 👉Review https://t.ly/UvXNS 👉Paper https://arxiv.org/pdf/2510.15018 👉Project https://urbanverseproject.github.io/ 👉Repo TBA

17 168

🫙Universal Feature Up-Sampling🫙 👉AnyUp is a novel method for feature up-sampling that can be applied to ANY vision feature at ANY resolution, without encoder-specific training: inference-time feature-agnostic up-sampling architecture to improve up-sampling quality. Repo under CC-4.0💙 👉Review https://t.ly/HvEw9 👉Paper https://arxiv.org/pdf/2510.12764 👉Project https://wimmerth.github.io/anyup/ 👉Repo https://github.com/wimmerth/anyup

17 168

🫧🫧 Detect Anything via MLLM 🫧🫧 👉Rex-Omni is a 3B-multimodal model that unifies visual perception tasks, including object detection, OCR, pointing, key-pointing & visual prompting into a single next point prediction framework. Impressive results. Full repo under IDEA License 1.0💙 👉Review https://t.ly/DCTk_ 👉Paper https://lnkd.in/d4VDD-9j 👉Project https://lnkd.in/d6unEyvq 👉Repo https://lnkd.in/dkYJFe-x

17 168

↗️ TrackVLA++ Visual Tracking↘️ 👉TrackVLA++ is a novel Vision-Language-Action model that incorporates spatial reasoning and target identification memory, enabling SOTA performance in both long-horizon and highly crowded tracking scenarios. Model announced💙 👉Review https://t.ly/ruYzc 👉Paper https://arxiv.org/pdf/2510.07134 👉Project pku-epic.github.io/TrackVLA-plus-plus-Web/ 👉Repo TBA

17 168

💄Pixel-Perfect Depth (SOTA)💄 👉Pixel-Perfect Depth is a mono-depth estimation model with pixel-space diffusion transformers. New SOTA. Repo under Apache 2.0💙 👉Review https://t.ly/75PGo 👉Paper https://lnkd.in/d8wxFpyY 👉Project https://lnkd.in/dV5HhsqH 👉Repo https://lnkd.in/d9JKFBJq 👉Demo https://lnkd.in/d3wBkKJ9

17 168

🎺Visual Grounding RVOS🎺 👉ReferDINO is a strong RVOS model that inherits region-level vision-language alignment from foundational visual grounding models, and is further endowed with pixel-level dense perception & cross-modal spatio-temporal reasoning. Code, Demo & checkpoints released💙 👉Review https://t.ly/rOdkP 👉Paper https://lnkd.in/efuAFQdE 👉Project https://lnkd.in/dK3wMZqv 👉Repo https://lnkd.in/d3i2PsNF

17 168

🎺Visual Grounding RVOS🎺 👉ReferDINO is a strong RVOS model that inherits region-level vision-language alignment from foundational visual grounding models, and is further endowed with pixel-level dense perception & cross-modal spatio-temporal reasoning. Code, Demo & checkpoints released💙 👉Review https://t.ly/rOdkP 👉Paper https://lnkd.in/efuAFQdE 👉Project https://lnkd.in/dK3wMZqv 👉Repo https://lnkd.in/d3i2PsNF

17 168

👉 A proof I'm not a bot... My (short) interview to one of the biggest Italian media: AI in 2016, HPC / Quantum and how I created my startup: https://www.linkedin.com/posts/visionarynet_ai-itw25-ai-activity-7381215486115643392-t7an Thanks for the support (and of course a new paper coming in a few hours)

17 168

🎷🎷 Clink! Chop! Thud! 🎷🎷 👉Sounding Object Detection: while an environment may contain many objects, only a few are directly involved in producing sound during an interaction. This model detects the sounding object given a video of an object interaction. Code/Data announced💙 👉Review https://t.ly/VK_1h 👉Paper https://lnkd.in/depNjVXm 👉Project https://lnkd.in/dF63EZFG 👉Repo TBA

17 168

🔩Code-Centric Agentic Education🔩 👉Show Lab unveils Code2Video: agentic, code-centric framework that generates HQ educational videos from knowledge points. Unlike pixel-based text-to-video models, this approach leverages executable Manim code to ensure clarity, coherence & reproducibility. Repo under MIT💙 👉Review https://t.ly/Fv4LJ 👉Paper https://arxiv.org/pdf/2510.01174 👉Repo https://github.com/showlab/Code2Video/ 👉Project https://showlab.github.io/Code2Video/

17 168

👩‍🦱Physical-Hair Diffusion👩‍🦱 👉CONTROLHAIR is novel hybrid framework that integrates a physics simulator with conditional video diffusion to enable controllable dynamic hair rendering. Repo announced💙 👉Review https://t.ly/78LHr 👉Paper https://lnkd.in/epm-A9Fq 👉Project https://lnkd.in/evsjz298 👉Repo TBA

17 168

👔 Universal Image Restoration 👔 👉LucidFlux by HKUSTGZ is the universal image restoration framework built on a large-scale diffusion transformer that delivers photorealistic restorations of real-world low-quality (LQ) images, outperforming SOTA diffusion-based models across diverse degradations. Repo under custom Non-Commercial License💙 👉Review https://t.ly/Z5cA3 👉Paper https://arxiv.org/pdf/2509.22414 👉Project https://w2genai-lab.github.io/LucidFlux/ 👉Repo https://github.com/W2GenAI-Lab/LucidFlux

17 168

🤖 Real-time Interactive Long Video 🤖 👉LONGLIVE by #Nvidia is a frame-level autoregressive framework for real-time & interactive long video generation. LONGLIVE accepts sequential user prompts and generates corresponding videos in real time. Repo under non-commercial license💙 👉Review https://t.ly/jJkdY 👉Paper arxiv.org/pdf/2509.22622 👉Project nvlabs.github.io/LongLive/ 👉Repo github.com/NVlabs/LongLive 🤗huggingface.co/Efficient-Large-Model/LongLive-1.3B

17 168

🔥SOTA Detection w/ DINOv3🔥 👉DEIMv2 is the evolution of DEIM framework while leveraging DINOv3. Various model sizes, from an ultra-light version up to S, M, L, & X for a wide range of scenarios. Across these variants, DEIMv2 achieves SOTA. Repo Apache2.0💙 👉Review https://t.ly/P7jEH 👉Paper arxiv.org/pdf/2509.20787 👉Repo github.com/Intellindust-AI-Lab/DEIMv2 👉Project intellindust-ai-lab.github.io/projects/DEIMv2