AI with Papers - Artificial Intelligence & Deep Learning
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All the AI with papers. Every day fresh updates on Deep Learning, Machine Learning, and Computer Vision (with Papers).

Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/
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🫀BlobGAN: Blob-Disentangled Scene🫀

👉Unsupervised, mid-level (blobs) generation of scenes

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Spatial, depth-ordered Gaussian blobs
Reaching for supervised level, and more
Source under BSD-2 "Simplified" License

More: https://bit.ly/3kRyGnj
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🦕E2EVE editor via pre-trained artist🦕

👉E2EVE generates a new version of the source image that resembles the "driver" one

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Blending regions by driver image
E2E cond-probability of the edits
S.S. augmenting in target domain
Implemented as SOTA transformer
Code/models available (soon)

More: https://bit.ly/3P9TDYW
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🐶 Bringing pets in #metaverse 🐶

👉ARTEMIS: pipeline for generating articulated neural pets for virtual worlds

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
ARTiculated, appEarance, Mo-synthesIS
Motion control, animation & rendering
Neural-generated (NGI) animal engine
SOTA animal mocap + neural control

More: https://bit.ly/3LZSLDU
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😍Animated hand in 1972, damn romantic😍

👉Q: is #VR the technology that developed least in the last 30 years? 🤔

More: https://bit.ly/3snxNaq
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⏏️Ensembling models for GAN training⏏️

👉Pretrained vision models to improve the GAN training. FID by 1.5 to 2×!

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
CV models as ensemble of discriminators
Improving GAN in limited / large-scale set
10k samples matches StyleGAN2 w/ 1.6M
Source code / models under MIT license

More: https://bit.ly/3wgUVsr
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🤯Cooperative Driving + AUTOCASTSIM🤯

👉COOPERNAUT: cross-vehicle perception for vision-based cooperative driving

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
UTexas + #Stanford + #Sony #AI
LiDAR into compact point-based
Network-augmented simulator
Source code and models available

More: https://bit.ly/3sr5HLk
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💄NeuralHDHair: 3D Neural Hair💄

👉NeuralHDHair: fully automatic system for modeling HD hair from a single image

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
IRHairNet for hair geometric features
GrowingNet: 3D hair strands in parallel
VIFu: novel voxel-aligned implicit function
SOTA in 3D hair modeling from single pic

More: https://bit.ly/38iR0mQ
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🐡DyNeRF: Neural 3D Video Synthesis🐡

👉#Meta unveils DyNeRF, novel rendering HQ 3D video

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Novel NeRF-based on temp-latent codes
Novel training based on hierarchical step
Datasets of time-synch/calibrated clips
Attribution-NonCommercial 4.0 Int.

More: https://bit.ly/3MlBRA9
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🍋GATO: agent for multiple tasks🍋

👉The same network with the same weights can play Atari, caption pics, chat, and more🤯

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
General-purpose agent, multiple tasks
Multi-modal-task, multi-embodiment
Inspired by large-scale language model

More: https://bit.ly/3LbBOWb
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🪐NeRF powered by keypoints🪐

👉ETHZ + META unveil how to encode relative spatial #3D info via sparse 3D keypoints

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Sparse 3D keypoints for SOTA avatars
Unseen subjects from 2/3 views
Never-before-seen iPhone captures

More: https://bit.ly/39NQqhe
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🐌Self-Supervised human co-evolution🐌

👉Self-supervised 3D by co-evolution of pose estimator, imitator, and hallucinator

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Novel self-supervised 3D pose
Co-evo of pose, imitator, hallucinator
Realist 3D pose and 2D-3D supervision
Source code / model under MIT license

More: https://bit.ly/37J5ImL
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🐲 Diff-SDF #3D Rendering 🐲

👉Reconstruction with no complex reg. or priors, using only a per-pixel RGB loss

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Diff-render to optimize geometry/albedo
No ad-hoc object mask or supervision
Extended sphere tracing algorithm

More: https://bit.ly/3yKWPnI
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👄LVD: new SOTA for #3D human👄

👉Corona et al. unveils a novel 3D human model fitting

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Solution via neural field
Not sensitive to initialization
SOTA in shape from single pic
SOTA in fitting 3D scans

More: https://bit.ly/3Ng4lLr
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🏳️‍🌈Deep Clustering on ImageNet & Co.🏳️‍🌈

👉World's first deep nonparametric clustering on large dataset such as ImageNet

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Deep clustering that infers nr. of clusters
Loss: amortized inference in mixt-models
Deep nonparametric clustering on ImageNet
Code and model available under MIT license

More: https://bit.ly/38p62rn
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💥HQ-E²FGVI just released💥💥

👉Flow-Guided Video Inpainting through three trainable modules

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
Flow, pixel-prop, content hallucination
Three stage-modules, jointly optimized
The new SOTA, promising efficiency
Code and Models under MIT license

More: https://bit.ly/3Ln0ICj
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🪔 AvatarCLIP: Text-Driven Avatar 🪔

👉Zero-shot text-driven for #3D avatar in #metaverse

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
First text-driven synthesis
Shape, texture, and motion
Animation-ready, HQ texture/geometry
Zero-shot text-guided ref-based motion
Code and model under MIT license

More: https://bit.ly/3LjTWgB
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🔥#AIwithPapers: we are 2,500!🔥

💙💛Only 2 Billion papers remaining on arXiv. The more we are, the faster we read💙💛

😈 Invite your friends -> https://t.me/AI_DeepLearning
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💥Podcasting AI & CV💥

👉🏼For people fluent in Italian: 1 hour podcast in which I talk about AI, CV, Startup and more (included this wonderful project).

More: https://bit.ly/38DtBwB
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🔥Inpainting: new SOTA! INSANE🔥

👉Novel two-stream approach: inpainting at the next level!

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
High-freq locally, low-freq globally
Local to global -> error correction
44% / 26% improvements FID/scores
Source code, more clips available

More: https://bit.ly/3ltIX9R
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