🔥 #AIwithPapers: we are 2,900+! 🔥

💙💛 Cheers from "Black Metal Lady Gaga" plotted by DallE-mini 💙💛

😈 Invite your friends -> https://t.me/AI_DeepLearning

🍅Segmentation with INSANE Occlusions🍅

👉CMU unveils WALT: segmenting in severe occlusion scenarios. Performance over human.

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅WALT: Watch & Learn Time-lapse
✅4K/1080p cams on streets over a year
✅Performance over human-supervised
✅Object-occluder-occluded neural layers
✅Source code under MIT license

More: https://bit.ly/3n7pvjO

🐠Largest Dataset for #autonomousdriving🐠

👉SHIFT: largest synthetic dataset for #selfdrivingcars. Shifts in cloud, rain, fog, time of day, vehicle & pedestrian density🤯

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅4,800+ clips, multi-view sensor suite
✅Semantic/instance, M/stereo depth
✅2D/3D object detection, MOT
✅Optical flow, point cloud registration
✅Visual-Odo, trajectory & human pose

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

🦑Big Egocentric Dataset by #Meta 🦑

👉Novel dataset to speed-up research on egocentric MR/AI

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅159 sequences, multiple sensors
✅Scenarios: cooking, exercising, etc.
✅‘Desktop Activities’ via multi-view mocap
✅Dataset available upon request

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

🦋Transf-Codebook HD-Face Restoration🦋

👉S-Lab unveils CodeFormer: hyper-datailed face restoration from degraded clips

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Face restoration as a code prediction
✅Discrete CB prior in small proxy space
✅Controllable transformation for LQ->HQ
✅Robustness and global coherence
✅Code and models soon available

More: https://bit.ly/3QEa9B5

🍔 Fully Controllable "NeRF" Faces 🍔

👉Neural control of pose/expressions from single portrait video

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅NeRF-control of the human head
✅Loss of rigidity by dynamic NeRF
✅3D full control/modelling of faces
✅No source code or models yet 😢

More: https://bit.ly/3OEjwi7

🫀I M AVATAR: source code is out!🫀

👉Neural implicit head avatars from monocular videos

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅#3D morphing-based implicit avatar
✅Detailed Geometry/appearance
✅D-Rendering e2e learning from clips
✅Novel synthetic dataset for evaluation

More: https://bit.ly/3A2yzy9

🗺️Neural Translation Image -> Map🗺️

👉A novel method for instantaneous mapping as a translation problem

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Bird’s-eye-view (BEV) map from image
✅A restricted data-efficient transformer
✅Monotonic attention from lang.domain
✅SOTA across several datasets

More: https://bit.ly/39MQ76Z

🥶 E2V-SDE: biggest troll ever? 🥶

👉E2V-SDE paper (accepted to #CVPR2022) consists of texts copied from 10+ previously published papers 😂

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Latent ODEs for Irregularly-Sampled TS
✅Stochastic Adversarial Video Prediction
✅Continuous Latent Process Flows
✅More papers....


More: https://bit.ly/3bsL8Zw (AUDIO ON!)

🔥🔥YOLOv6 is out: PURE FIRE!🔥🔥

👉YOLOv6 is a single-stage object detection framework for industrial applications

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Efficient Decoupled Head with SIoU Loss
✅Hardware-friendly for Backbone/Neck
✅520+ FPS on T4 + TensorRT FP16
✅Released under GNU General Public v3.0

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

🐪 BlazePose: Real-Time Human Tracking 🐪

👉Novel real-time #3D human landmarks from #google. Suitable for mobile.

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅MoCap from single RGB on mobile
✅Avatar, Fitness, #Yoga & AR/VR
✅Full body pose from monocular
✅Novel 3D ground truth acquisition
✅Additional hand landmarks
✅Fully integrated in #MediaPipe

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

🔥YOLOv7: YOLO for segmentation🔥

👉YOLOv7: adding a lot of newer skills to the YOLO architecture family.

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅YOLOv7, not a successor of YOLO family!
✅Framework for detection & segmentation
✅Applications based on #META detectron2
✅DETR & ViT detection out-of-box
✅Easy support for pipeline thought #ONNX
✅YOLOv4 + InstanceSegm. via single stage
✅The latest YOLOv6 training is supported!
✅Source code under GPL license.

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

🔥🔥 HD Dichotomous Segmentation 🔥🔥

👉 A new task to segment highly accurate objects from natural images.

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅5,000+ HD images + accurate binary mask
✅IS-Net baseline in high-dim feature spaces
✅HCE: model vs. human interventions
✅Source code (should be) available soon

More: https://bit.ly/3ah2BDO

🔥🔥 Neural Segmentation on fire 🔥🔥

👉Novel methods for segmentation with mask calibration. Robustness++ in VOS.

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Study: VOS robustness vs. perturbations
✅Adaptive object proxy (AOP) aggregation
✅Less errors due unstable pixel-level match
✅Code/models (should be) available soon

More: https://bit.ly/3yhIY6Q

😊😎 Seq-DeepFake via Transformers 😎😊

👉S-Lab opens Seq-DeepFake: Detecting Sequential DeepFake Manipulation

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Seq-DeepFake: sequences of facial edits
✅Dataset: 85k #deepfake manipulation
✅Powerful Seq-DeepFake Transformer
✅Code, dataset and models available!

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

🦒 Text2LIVE: Text-Driven Neural Editing 🦒

👉#Amazon unveils a novel #AI for text-driven edit of videos. Insane! 🤯

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Semantic edits of real-world videos
✅Edit layer–RGBA representing target
✅Edit layers synthesized on single input
✅No masks or a pre-trained generator

More: https://bit.ly/3NVP6aE

📟📟AI-Designed Circuits with Deep RL📟📟

👉#Nvidia unveils an #AI to design circuits from scratch, smaller and faster than SOTA ones

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Parallel prefix circuits for Hi-Perf
✅RL framework to explore the circuit space
✅Smaller, Faster, Power-- from the scratch

More: https://bit.ly/3yY9dk7

👽 Neural I2I with a few shoots 👽

👉#Alibaba unveils a novel portrait stylization. Limited samples (∼100) -> HD outputs

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Calibration first, translation later
✅Balanced distribution to calibrate bias
✅Spatially semantic constraints via geometry
✅Source code and models soon available!

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

🤹‍♂️ K-Means Mask Transformer 🤹‍♂️

👉#Google AI unveils kMaX-DeepLab, novel E2E method for segmentation

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅kMaX-DeepLab: k-means Mask Xformer
✅Rethinking relationship pixels / object
✅Cross-attention -> k-means clustering
✅The new SOTA on several dataset

More: https://bit.ly/3O2QV5I