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 17 265 名订阅者，在 技术与应用 类别中位列第 7 532，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 17 265 名订阅者。
根据 29 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 219，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 16.46%。内容发布后 24 小时内通常能获得 7.09% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 2 842 次浏览，首日通常累积 1 223 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 17。
- 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 30 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。
17 265
订阅者
无数据24 小时
+27 天
+21930 天
帖子存档
🦉PANDORA: Polarized Neural Decomposition🦉
👉CIL lab unveils PANDORA: polarimetric inverse rendering approach via INR
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Geometry, reflectance & illumination
✅normal, signed distance field, mesh
✅Diffuse-specular separation
✅Hi-fI incident illumination
More https://bit.ly/3CzGp3F
🍈 #StableDiffusion archive is out🍈
👉Lexica art is a Stable Diffusion prompt search engine. Real-time, countless #stablediffusion results for everyone. I had fun with the GOAT, #Maradona.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Maradona scoring against a capybara...
✅A poster of space jam with Maradona...
✅Painting of Maradona very detailed...
✅Painting of Maradona in heaven...
More: https://bit.ly/3PTXHLH
🌐RelPose: Probabilistic Relative Pose🌐
👉A novel method for core component in #SLAM / NeRF-powered apps.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Core component of SfM/SLAM
✅Pre-processing for neural (NeRF)
✅Energy-based over rotations
✅SOTA on both seen/unseen objects
More: https://bit.ly/3T60TXw
🍈DeepBillboards: old-school trick for #VR🍈
👉DeepBillboards models a 3D object implicitly using neural net on the user’s viewing direction
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅#Google Brain +Tsukuba + Tokyo
✅Rendering at higher res., improving #VR
✅NeRF into interactive VR with accuracy++
✅NeRF (or any others) directly in #Unity
More: https://bit.ly/3CsTQ5y
🥭Massive GTA-V human dataset🥭
👉GTA-Human: outperforming SOTA with a purely synthetic training.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅600+ gender, age, ethnicity & clothing
✅20,000+ clips, variety of human activities
✅6 categories of location, different BGs
✅Occlusions, lighting, and weather system
More: https://bit.ly/3wpZyRD
🔥 KeypointNeRF: code is out! 🔥
👉KeypointNeRF by #Meta: "NeRF"-avatars
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Generalizable NeRF for virtual avatar
✅Sparse 3D keypoints for SOTA avatar
✅Novel unseen subjects from 2/3 views
✅"iPhone" captures for #metaverse
More: https://bit.ly/3pyl17e
🔥🔥UPDATE🔥🔥
Code Released: https://github.com/facebookresearch/KeypointNeRF
🥑 CLIP-based Neural Style Transfer 🥑
👉From #Nvidia a novel method for transferring the style to a #3D object
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Texture style for 3D by CLIP-ResNet50
✅Nearest-neighbor feature matching loss
✅CLIP-based loss extraction of textures
✅NNFM for multiple style pics / control
✅No source code or models available 😒
More: https://bit.ly/3c32dK5
🍏NeuMan: Human NeRF in the wild🍏
👉#Apple opens a novel human pose/view from just a single in-the-wild video
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅No extra devices/annotations
✅Both Human (novel poses) + Scene
✅E2E SMPL optimization + error-corr.
✅Applications such as "telegathering"
More: https://bit.ly/3K4iTO6
🧰 FGT: flow-guided inpainting 🧰
👉#Microsoft (+USTC) unveils FGT: flow-guided ViT for video inpainting 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅OF into transformer for attention++
✅Flow completion net w/ local feats.
✅Dual perspective spatial MHSA
✅Local attention with global content
More: https://bit.ly/3pk5J5S
🐍 Implicitron: "democratizing" NeRF🐍
👉#META opens a novel framework for NeRF-world in #PyTorch3D #pytorch
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Implicit representations (NeRF) / Render
✅RaySampler/PointSampler & more
✅NeRF’s MLP, IDR’s FF, SRN, etc.
✅Renderers: MEAR, LSTMRenderer, etc.
More: https://bit.ly/3bPyJPJ
🔥Stable Diffusion on clips. INSANE🔥
👉The most advanced latent text-to-image DM. #RunwayML just announced is going to apply it on clips
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Latent DM on 512p from LAION-5B
✅Frozen CLIP ViT-L/14 text encoder
✅Lightweight, runs on a 10GB-GPU
✅Checkpoints only for research
More: https://bit.ly/3QfkRx3
🍨 Scaling Neural Indoor Scene 🍨
👉Neural scene rendering for indoor: scalable in both training/rendering
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Neural scene rendering for indoor
✅#3D into tiles with MLPs to scale up
✅Parallel training of tile-based MLPs
✅View-indep. components (via surf-MLP)
More: https://bit.ly/3bH94IX
🎰 Texturify: Neural Textures Generator 🎰
👉A step towards automated content creation. HQ textures directly on surface of 3D object
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅TUM + Max Planck + Apple 🍏
✅Realistic, HQ textures from 2D pics
✅3D shape geometry, no 3D supervision
✅3D-aware surface-based generation net
More: https://bit.ly/3BW7UUU
🪰 EasyMocap: Open Neural Mocap 🪰
👉EasyMocap: open-source marker-less mocap with novel view synthesis from RGB
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬 (of last paper added):
✅Editable free-viewpoint video
✅Layered neural representation of humans
✅Multi-pax -> instances, weakly-supervised
✅HQ neural representation of the humans
✅Addressing camera error by human poses
More: https://bit.ly/3p6lUDO
🥇#NVIDIA wins SIGGRAPH's Best Paper🥇
👉Instant #NeRF awarded as a best paper at SIGGRAPH 2022!
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Speed-up of several orders of magnitude
✅HQ neural primitives in a matter of secs
✅Render in tens of milliseconds at 1080p
✅Source code and resources available!
More: https://bit.ly/3Qt8c9D
🧊EPro-PnP: Persp-n-Points Detection🧊
👉EPro-PnP: probabilistic PnP layer for general e2e pose estimation
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Probabilistic PnP for general e2e pose
✅Top-tier in 6DoF by inserting into CDPN
✅Deformable accurate detection
✅2D-3D corresp. learned from scratch
More: https://bit.ly/3BNPXYr
🎹🎹 Learning Piano in #AR 🎹🎹
👉PianoVision (on #META #Quest2) accelerates the piano learning via Passthrough #AR & hand tracking
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Sheet Insight to learn sight-read
✅MIDI keyboard connectivity
✅Air piano for no physical pianos
✅Multiplayer Music Instruction
✅PianoVision Music Hall in #VR
More: https://bit.ly/3zYvwGX
🍑 World-Object Detection via ViT 🍑
👉Google unveils OWL-ViT: open-vocabulary detector based on ViTs 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅ViTs for Open-World Localization
✅Img-level to open-vocabulary detection
✅SOTA one-shot (img.cond.) detection
More: https://bit.ly/3Sy3jOj
