AI with Papers - Artificial Intelligence & Deep Learning
前往频道在 Telegram
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
显示更多📈 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 17 262 名订阅者，在 技术与应用 类别中位列第 7 491，并在 马来西亚 地区排名第 2 128 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 17 262 名订阅者。
根据 23 十月, 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 255，过去 24 小时变化为 2，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 18.93%。内容发布后 24 小时内通常能获得 7.17% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 3 267 次浏览，首日通常累积 1 237 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 20。
- 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 24 十月, 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。
17 262
订阅者
+224 小时
+67 天
+25530 天
帖子存档
🔥Orient Anything V2 is out🔥
👉Orient Anything V2 is a foundation model for unified understanding of object 3D orientation and rotation from single or paired images. Repo under CC-BY-4.0💙
👉Review https://t.ly/Ht7Xd
👉Paper arxiv.org/pdf/2601.05573
👉Project orient-anythingv2.github.io/
👉Repo github.com/SpatialVision/Orient-Anything-V2
🔥 New #AI Startups in 2026? 🔥
In 2026, which area would you focus on?
🤖Agents → workflows, copilots, etc.
🏭Vertical AI → Pharma, Automotive, Energy ...
🧠Infrastructure → MLOps, Security, Cost Control ...
🎨AI for Creators/Media → Video, avatars, contents ...
Please, help me understanding what's next with this poll on LinkedIn :)
https://www.linkedin.com/posts/visionarynet_ai-ai-deeplearning-activity-7415377341779996672-sQO1
LUV U \m/
🌍Label Any Object in 3D 🌍
👉LabelAny3D: novel analysis-by-synthesis framework that reconstructs holistic 3D scenes from 2D to efficiently produce HQ 3D BBs annotations. Repo under CC-BY-4.0 license💙
👉Review https://t.ly/bO93j
👉Paper https://lnkd.in/dYb97zWG
👉Project https://lnkd.in/dJ9UKERb
👉Repo https://lnkd.in/d9SxtmiA
🦙 Depth as Neural Implicit 🦙
👉InfiniDepth represents depth as neural implicit fields, "infinite" (i.e.16K) resolution and geometrical details. Repo under Apache 2.0💙
👉Review https://t.ly/4we5t
👉Paper https://lnkd.in/dpiHQExj
👉Project https://lnkd.in/dy3JxKye
👉Repo https://lnkd.in/dAXbnK5z
⭐ TOP 5 Papers you loved in 2025 ⭐
👉 In 2025 novel architectures have redefined efficiency and accuracy, and almost every day brought a new SOTA in image understanding, tracking, and #GenAI. It’s been an inspiring ride, and 2026 it will be even wilder. This community (LinkedIn + Telegram) is now around 80,000+ people.
𝐏𝐚𝐩𝐞𝐫𝐬 (𝐛𝐲 𝐲𝐨𝐮𝐫 𝐩𝐫𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞):
⭐3D LLM Understanding https://t.ly/ejr1s
⭐DynOMo is out https://t.ly/t5pCf
⭐Tracking Transformations https://t.ly/NPyW4
⭐YOLOv12 (new SOTA) https://t.ly/jj1oR
⭐Gaussian Surface Tracking https://t.ly/udpMq
Thank you all💙
🎯Generative Refocusing is out🎯
👉Generative Refocusing is a two-step process that uses DeblurNet to recover all-in-focus images from various inputs and BokehNet for creating controllable bokeh (in semi-supervised mode). Repo under Apache2.0💙
👉Review https://t.ly/8t7PA
👉Paper arxiv.org/pdf/2512.16923
👉Project generative-refocusing.github.io/
👉Repo github.com/rayray9999/Genfocus
👉Demo huggingface.co/spaces/nycu-cplab/Genfocus-Demo
🏜️ Depth Any Panoramas 🏜️
👉DAP is the new SOTA foundation model for panoramic depth estimation with a large scale dataset. Data & Repo under MIT💙
👉Review https://t.ly/LaUmd
👉Paper arxiv.org/pdf/2512.16913
👉Project https://lnkd.in/dvqNV9jx
👉Repo https://lnkd.in/dmNzhb-7
👉Demo https://lnkd.in/dDwjMF3u
🫠 FlexAvatar: 3D Heads Avatars 🫠
👉TUM introduces FlexAvatar, a novel method for creating HQ and complete 3D head avatars from a single image. Code announced💙
👉Review https://t.ly/Rkdtd
👉Paper arxiv.org/pdf/2512.15599
👉Project tobias-kirschstein.github.io/flexavatar/
👉Repo TBA
👀DriverGaze360: Driver SOTA👀
👉DriverGaze360 is a large-scale 360◦ field of view driver attention dataset, containing ∼1M gaze-labeled frames. Code & Dataset announced💙
👉Review https://t.ly/ZcoUw
👉Paper arxiv.org/pdf/2512.14266
👉Project av.dfki.de/drivergaze360/
👉Repo github.com/dfki-av/drivergaze360
👉Data av.dfki.de/drivergaze360/dataset
💷 SOTA Zero-Shot Stereo Matching💷
👉Fast-FoundationStereo by #Nvidia is a novel family of architectures that achieve, for the first time, strong zero-shot generalization at real-time frame rate via divide-&-conquer acceleration. Code & Data announced💙
👉Review https://t.ly/XD6pO
👉Paper https://lnkd.in/d9_YKW2A
👉Project https://lnkd.in/dKDxm7EX
👉Repo https://lnkd.in/dR4-PdsW
💚 MatAnyone 2 is out! 💚
👉MatAnyone 2 is the most advanced human video matting framework that preserves fine details by avoiding segmentation-like boundaries, while also shows enhanced robustness under challenging real-world conditions. Repo & Dataset announced💙
👉Review https://www.linkedin.com/posts/visionarynet_artificialintelligence-ai-deeplearning-activity-7406244283055525888-8Dl_
👉Paper arxiv.org/pdf/2512.11782
👉Project pq-yang.github.io/projects/MatAnyone2
👉Repo github.com/pq-yang/MatAnyone2
🫎 MoCapAnything is out 🫎
👉MoCapAnything is novel a reference-guided, factorized framework that first predicts 3D joint trajectories and then recovers asset-specific rotations via constraint-aware IK fitting. No code announced 🥲
👉Review https://t.ly/_Tw6t
👉Paper arxiv.org/pdf/2512.10881
👉Project animotionlab.github.io/MoCapAnything
🧱 Pixel Art Volumetric Rendering 🧱
👉Voxify3D is a novel differentiable two-stage framework bridging 3D mesh optimization with 2D pixel art supervision. Repo announced💙
👉Review https://t.ly/qPyNl
👉Paper https://lnkd.in/du5ikJGN
👉Project https://lnkd.in/dpiAjj5m
👉Repo TBA
🎷Layered PSD Diffusion🎷
👉OmniPSD produces layered PSD files with transparent alpha channels, separating text, foreground elements, and background into clean RGBA layers that can be directly edited in tools. Online Demo💙
👉Review https://t.ly/YNRAC
👉Paper arxiv.org/pdf/2512.09247
👉Project showlab.github.io/OmniPSD/
👉Demo https://www.lovart.ai/it
🐘TTSC for 3D Generative🐘
👉SpaceControl is the new SOTA training-free test-time method for explicit spatial control of 3D generation. Repo announced💙
👉Review https://t.ly/1zrah
👉Paper https://lnkd.in/dEWh3vep
👉Project https://lnkd.in/dScftUmm
👉Repo TBA
✌️SOTA Generative SLP✌️
👉Stable Signer is a new sign language generative model. It redefines the SLP task as a hierarchical generation end-to-end task that only includes text understanding (Prompt2Gloss, Text2Gloss) and Pose2Vid. Repo with data 💙
👉Review https://t.ly/yKZhn
👉Paper arxiv.org/pdf/2512.04048
👉Project stablesigner.github.io/
👉Data github.com/SignLLM/Prompt2Sign/tree/main/tools-new-2025
🦄 Native Unified Multimodal 🦄
👉META unveils a novel UMM that builds a unified continuous visual representation by cascading a VAE encoder with a representation encoder. This unified representation space allows E2E processing of images/videos for both understanding/generation. Code under legal review💙
👉Review https://t.ly/7wmKP
👉Paper https://lnkd.in/djT4WGEU
👉Project https://tuna-ai.org/
👉Repo github.com/wren93/tuna
🥭3D Point Motion Editing🥭
👉Edit-by-Track enables precise video motion editing via 3D point tracks. By specifying desired 3D trajectories, users can seamlessly control joint camera and object motion, remove objects, and transfer motion between videos. No code announced but it's a relevant paper💙
👉Review https://t.ly/lqzHY
👉Paper https://arxiv.org/pdf/2512.02015
👉Project https://edit-by-track.github.io/
