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 17 261 名订阅者，在 技术与应用 类别中位列第 7 500，并在 马来西亚 地区排名第 2 124 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 17 261 名订阅者。
根据 24 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 258，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 16.76%。内容发布后 24 小时内通常能获得 7.11% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 2 893 次浏览，首日通常累积 1 227 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 16。
- 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 25 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。
17 261
订阅者
-224 小时
+27 天
+25830 天
帖子存档
🧿 Look Ma, no markers 🧿
👉#Microsoft unveils the first technique for marker-free, HQ reconstruction of COMPLETE human body, including eyes and tongue, without requiring any calibration, manual intervention or custom hardware. Impressive results! Repo for training & Dataset released💙
👉Review https://t.ly/5fN0g
👉Paper arxiv.org/pdf/2410.11520
👉Project microsoft.github.io/SynthMoCap/
👉Repo github.com/microsoft/SynthMoCap
🔥BitNet: code of 1-bit LLM is out 🔥
👉BitNet by #Microsoft, announced in late 2023, is a 1-bit Transformer architecture designed for LLMs. BitLinear as a drop-in replacement of the nn.Linear layer in order to train 1-bit weights from scratch. Source Code just released a few hours ago 💙
👉Review https://t.ly/3G2LA
👉Paper arxiv.org/pdf/2310.11453
👉Code https://lnkd.in/duPADJVb
☀️ GS + Depth = SOTA ☀️
👉ETH unveils DepthSplat, the new SOTA in depth estimation and novel view synthesis tasks. The key feature is the cross-task interactions between Gaussian Splatting & depth estimation. Source Code to be released in a few days💙
👉Review https://t.ly/87HuH
👉Paper arxiv.org/abs/2410.13862
👉Project haofeixu.github.io/depthsplat/
👉Code github.com/cvg/depthsplat
🦠 Neural Metamorphosis 🦠
👉NU Singapore unveils NeuMeta to transform neural nets by allowing a single model to adapt on the fly to different sizes, generating the right weights when needed.
👉Review https://t.ly/DJab3
👉Paper arxiv.org/pdf/2410.11878
👉Project adamdad.github.io/neumeta
👉Code github.com/Adamdad/neumeta
🔥 CoTracker3 by #META is out! 🔥
👉#Meta (+VGG Oxford) unveils CoTracker3, a new tracker that outperforms the previous SoTA by a large margin using only the 0.1% of the training data 🤯🤯🤯
👉Review https://t.ly/TcRIv
👉Paper arxiv.org/pdf/2410.11831
👉Project cotracker3.github.io/
👉Code github.com/facebookresearch/co-tracker
🪞Robo-Emulation via Video Imitation🪞
👉OKAMI (UT & #Nvidia) is a novel foundation method that generates a manipulation plan from a single RGB-D video and derives a policy for execution.
👉Review https://t.ly/_N29-
👉Paper arxiv.org/pdf/2410.11792
👉Project https://lnkd.in/d6bHF_-s
🔥 DEPTH ANY VIDEO is out! 🔥
👉DAV is a novel foundation model for image/video depth estimation.The new SOTA for accuracy & consistency, up to 150 FPS!
👉Review https://t.ly/CjSz2
👉Paper arxiv.org/pdf/2410.10815
👉Project depthanyvideo.github.io/
👉Code github.com/Nightmare-n/DepthAnyVideo
🥎POKEFLEX: Soft Object Dataset🥎
👉PokeFlex from ETH is a dataset that includes 3D textured meshes, point clouds, RGB & depth maps of deformable objects. Pretrained models & dataset announced💙
👉Review https://t.ly/GXggP
👉Paper arxiv.org/pdf/2410.07688
👉Project https://lnkd.in/duv-jS7a
👉Repo
💡Diffusion Models Relighting💡
👉#Netflix unveils DifFRelight, a novel free-viewpoint facial relighting via diffusion model. Precise lighting control, high-fidelity relit facial images from flat-lit inputs.
👉Review https://t.ly/fliXU
👉Paper arxiv.org/pdf/2410.08188
👉Project www.eyelinestudios.com/research/diffrelight.html
🥦Gaussian Splatting VTON🥦
👉GS-VTON is a novel image-prompted 3D-VTON which, by leveraging 3DGS as the 3D representation, enables the transfer of pre-trained knowledge from 2D VTON models to 3D while improving cross-view consistency. Code announced💙
👉Review https://t.ly/sTPbW
👉Paper arxiv.org/pdf/2410.05259
👉Project yukangcao.github.io/GS-VTON/
👉Repo github.com/yukangcao/GS-VTON
🐏 EFM3D: 3D Ego-Foundation 🐏
👉#META presents EFM3D, the first benchmark for 3D object detection and surface regression on HQ annotated egocentric data of Project Aria. Datasets & Code released💙
👉Review https://t.ly/cDJv6
👉Paper arxiv.org/pdf/2406.10224
👉Project www.projectaria.com/datasets/aeo/
👉Repo github.com/facebookresearch/efm3d
🔥 "Deep Gen-AI" Full Course 🔥
👉A fresh course from Stanford about the probabilistic foundations and algorithms for deep generative models. A novel overview about the evolution of the genAI in #computervision, language and more...
👉Review https://t.ly/ylBxq
👉Course https://lnkd.in/dMKH9gNe
👉Lectures https://lnkd.in/d_uwDvT6
🛳️ EVER Ellipsoid Rendering 🛳️
👉UCSD & Google present EVER, a novel method for real-time differentiable emission-only volume rendering. Unlike 3DGS it does not suffer from popping artifacts and view dependent density, achieving ∼30 FPS at 720p on #NVIDIA RTX4090.
👉Review https://t.ly/zAfGU
👉Paper arxiv.org/pdf/2410.01804
👉Project half-potato.gitlab.io/posts/ever/
🦴 One-Image Object Detection 🦴
👉Delft University (+Hensoldt Optronics) introduces OSSA, a novel unsupervised domain adaptation method for object detection that utilizes a single, unlabeled target image to approximate the target domain style. Code released💙
👉Review https://t.ly/-li2G
👉Paper arxiv.org/pdf/2410.00900
👉Code github.com/RobinGerster7/OSSA
🍇SPARK: Real-time Face Capture🍇
👉Technicolor Group unveils SPARK, a novel high-precision 3D face capture via collection of unconstrained videos of a subject as prior information. New SOTA able to handle unseen pose, expression and lighting. Impressive results. Code & Model announced💙
👉Review https://t.ly/rZOgp
👉Paper arxiv.org/pdf/2409.07984
👉Project kelianb.github.io/SPARK/
👉Repo github.com/KelianB/SPARK/
👩🦰 SOTA Gaussian Haircut 👩🦰
👉ETH et. al unveils Gaussian Haircut, the new SOTA in hair reconstruction via dual representation (classic + 3D Gaussian). Code and Model announced💙
👉Review https://t.ly/aiOjq
👉Paper arxiv.org/pdf/2409.14778
👉Project https://lnkd.in/dFRm2ycb
👉Repo https://lnkd.in/d5NWNkb5
🌾 New SOTA Edge Detection 🌾
👉CUP (+ ESPOCH) unveils the new SOTA for Edge Detection (NBED); superior performance consistently across multiple benchmarks, even compared with huge computational cost and complex training models. Source Code released💙
👉Review https://t.ly/zUMcS
👉Paper arxiv.org/pdf/2409.14976
👉Code github.com/Li-yachuan/NBED
🩰 Dressed Humans in the wild 🩰
👉ETH (+ #Microsoft ) ReLoo: novel 3D-HQ reconstruction of humans dressed in loose garments from mono in-the-wild clips. No prior assumptions about the garments. Source Code announced, coming 💙
👉Review https://t.ly/evgmN
👉Paper arxiv.org/pdf/2409.15269
👉Project moygcc.github.io/ReLoo/
👉Code github.com/eth-ait/ReLoo
🎢 Robo-quadruped Parkour🎢
👉LAAS-CNRS unveils a novel RL approach to perform agile skills that are reminiscent of parkour, such as walking, climbing high steps, leaping over gaps, and crawling under obstacles. Data and Code available💙
👉Review https://t.ly/-6VRm
👉Paper arxiv.org/pdf/2409.13678
👉Project gepetto.github.io/SoloParkour/
👉Code github.com/Gepetto/SoloParkour
🌏 JoyHallo: Mandarin Digital Human 🌏
👉JD Health faced the challenges of audio-driven video generation in Mandarin, a task complicated by the language’s intricate lip movements and the scarcity of HQ datasets. Impressive results (-> audio ON). Code Models available💙
👉Review https://t.ly/5NGDh
👉Paper arxiv.org/pdf/2409.13268
👉Project jdh-algo.github.io/JoyHallo/
👉Code github.com/jdh-algo/JoyHallo
