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
Show more📈 Analytical overview of Telegram channel AI with Papers - Artificial Intelligence & Deep Learning
Channel AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) in the English language segment is an active participant. Currently, the community unites 17 261 subscribers, ranking 7 532 in the Technologies & Applications category and 2 128 in the Malaysia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 17 261 subscribers.
According to the latest data from 29 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 219 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 16.46%. Within the first 24 hours after publication, content typically collects 7.09% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 842 views. Within the first day, a publication typically gains 1 223 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 17.
- Thematic interests: Content is focused on key topics such as framework, object, dataset, tba, depth.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“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”
Thanks to the high frequency of updates (latest data received on 30 October, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
17 261
Subscribers
No data24 hours
+27 days
+21930 days
Posts Archive
🦉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
