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☕ORViT for understanding tasks☕
👉ORViT: object-centric approach that extends ViT layers incorporating object representations
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Spatio-temporal through the net
✅''Object-Region Attention''
✅''Object-Dynamics" module
✅Code just released! Apache 2.0
More: https://bit.ly/3wAUavW
👉ORViT: object-centric approach that extends ViT layers incorporating object representations
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Spatio-temporal through the net
✅''Object-Region Attention''
✅''Object-Dynamics" module
✅Code just released! Apache 2.0
More: https://bit.ly/3wAUavW
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🪅Insane Neural Sketching from #MIT🪅
👉Line drawing generation as unsupervised image translation with various losses
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Unpaired method for line drawing
✅Geometry loss to predict depth
✅Semantic loss to match CLIP feats
✅SOTA on unpaired translation/generation
✅Code and Models under MIT License
More: https://bit.ly/36JRr8A
👉Line drawing generation as unsupervised image translation with various losses
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Unpaired method for line drawing
✅Geometry loss to predict depth
✅Semantic loss to match CLIP feats
✅SOTA on unpaired translation/generation
✅Code and Models under MIT License
More: https://bit.ly/36JRr8A
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🏔️MPS-Net: new SOTA for #3D human🏔️
👉MPS-Net: accurate & temporally coherent 3D human pose/shape from video
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅MoCA: visual cues from motion
✅HAFI to mix past/future feats
✅Stronger temporal correlation
✅SOTA on multiple datasets
More: https://bit.ly/3uAI5EB
👉MPS-Net: accurate & temporally coherent 3D human pose/shape from video
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅MoCA: visual cues from motion
✅HAFI to mix past/future feats
✅Stronger temporal correlation
✅SOTA on multiple datasets
More: https://bit.ly/3uAI5EB
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🤿Transfiner: hyper-detailed segmentation🤿
👉Mask Transfiner: #AI for HQ & efficient instance segmentation
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Transfiner: HQ segmentation
✅HQ seg. via quadtree structure
✅SOTA & extreme details
✅Code under MIT License
More: https://bit.ly/3KVzseM
👉Mask Transfiner: #AI for HQ & efficient instance segmentation
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Transfiner: HQ segmentation
✅HQ seg. via quadtree structure
✅SOTA & extreme details
✅Code under MIT License
More: https://bit.ly/3KVzseM
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🥙 DualStyleGAN: SOTA in style transfer🥙
👉Flexible control of dual styles of face domain and extended artistic portrait domain
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅High-resolution (1024*1024)
✅Intrinsic/extrinsic style path
✅Hierarchical style manipulation
✅Novel progressive fine-tuning
✅Source code under MIT License
More: https://bit.ly/3uS26Xp
👉Flexible control of dual styles of face domain and extended artistic portrait domain
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅High-resolution (1024*1024)
✅Intrinsic/extrinsic style path
✅Hierarchical style manipulation
✅Novel progressive fine-tuning
✅Source code under MIT License
More: https://bit.ly/3uS26Xp
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🍚 GTR: Global Tracking Transformers 🍚
👉UTexas + Apple: transformer for global multi-object tracking
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅GTR operates on any object
✅Few frames->global trajectories
✅SOTA on detectors for any object
✅Code under Apache License 2.0
More: https://bit.ly/3DiqkxF
👉UTexas + Apple: transformer for global multi-object tracking
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅GTR operates on any object
✅Few frames->global trajectories
✅SOTA on detectors for any object
✅Code under Apache License 2.0
More: https://bit.ly/3DiqkxF
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🧠E2E Perception for #selfdrivingcars🧠
👉HybridNets: multi-task net with several key optimizations
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅End-to-end perception network
✅Traffic, lane, object detection
✅Drivable segmentation area
✅Real-time on embedded systems
✅Source code under MIT License
More: https://bit.ly/3JMk8Az
👉HybridNets: multi-task net with several key optimizations
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅End-to-end perception network
✅Traffic, lane, object detection
✅Drivable segmentation area
✅Real-time on embedded systems
✅Source code under MIT License
More: https://bit.ly/3JMk8Az
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🛩️Smart Parking with UAVs🛩️
👉A novel methodology to monitor car parking areas in real-time via Drones/UAVs
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅YoloV3 + DeepSort tracker
✅Vehicle detection/tracking
✅Occupancy estimation via RT
✅Four blocks, unique pipeline
More: https://bit.ly/3iJD8nm
👉A novel methodology to monitor car parking areas in real-time via Drones/UAVs
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅YoloV3 + DeepSort tracker
✅Vehicle detection/tracking
✅Occupancy estimation via RT
✅Four blocks, unique pipeline
More: https://bit.ly/3iJD8nm
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👕 Detecting Events via #AI 👕
👉Localizing object states & corresponding state-modifying actions
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅SS-learning state-modifying
✅Noise adaptive weighting
✅ChangeIt: 2.6k+ hrs , 34k+ changes
✅Dataset, code, and model!
More: https://bit.ly/3uBwxkj
👉Localizing object states & corresponding state-modifying actions
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅SS-learning state-modifying
✅Noise adaptive weighting
✅ChangeIt: 2.6k+ hrs , 34k+ changes
✅Dataset, code, and model!
More: https://bit.ly/3uBwxkj
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🌈🌈 Interactive Neural Labelling 🌈🌈
👉Dense labelling of geometry, color & semantics via #3D neural field
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅No training data
✅Dense labeling
✅Classes on the fly
✅Labelling at a scale
More: https://bit.ly/36Y0faQ
👉Dense labelling of geometry, color & semantics via #3D neural field
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅No training data
✅Dense labeling
✅Classes on the fly
✅Labelling at a scale
More: https://bit.ly/36Y0faQ
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♟️Neural RGB-D Reconstruction♟️
👉Novel approach for #3D mixing implicit surface representations with NeRFs
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅RGB-D based reconstruction
✅Leveraging color & depth
✅Depth into the NeRF
✅Pose & camera refinement
More: https://bit.ly/3iN6e54
👉Novel approach for #3D mixing implicit surface representations with NeRFs
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅RGB-D based reconstruction
✅Leveraging color & depth
✅Depth into the NeRF
✅Pose & camera refinement
More: https://bit.ly/3iN6e54
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🦓 Hyper-Fast Refinement 🦓
👉SharpContour: novel contour-based refinement for semantic segmentation
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Instance-aware Point Classifier
✅Deforming by discrete updating
✅Estimating offsets independently
✅Source code soon available!
More: https://bit.ly/3qL04GY
👉SharpContour: novel contour-based refinement for semantic segmentation
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Instance-aware Point Classifier
✅Deforming by discrete updating
✅Estimating offsets independently
✅Source code soon available!
More: https://bit.ly/3qL04GY
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🥗 Neural Mesh via Text only 🥗
👉Zero-shot generation of 3D model using only a target text prompt
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅ZS 3D model with text only
✅ZS text-guided generation
✅Meshes with texture/normal
✅Differentiable LLS implementation
More: https://bit.ly/3u0qnvb
👉Zero-shot generation of 3D model using only a target text prompt
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅ZS 3D model with text only
✅ZS text-guided generation
✅Meshes with texture/normal
✅Differentiable LLS implementation
More: https://bit.ly/3u0qnvb
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🪆#3D, Materials, and Lighting from 2D🪆
👉Nvidia: topology, materials & map lighting jointly from 2D. INSANE 😮
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Topology, materials and lighting
✅Meshes with materials/lighting
✅Compact volumetric texturing
✅Differentiable all-frequency lighting
✅Code under #NVIDIA License
More: https://bit.ly/3IUoF2t
👉Nvidia: topology, materials & map lighting jointly from 2D. INSANE 😮
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Topology, materials and lighting
✅Meshes with materials/lighting
✅Compact volumetric texturing
✅Differentiable all-frequency lighting
✅Code under #NVIDIA License
More: https://bit.ly/3IUoF2t
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🍜Ref-NeRF for extreme realism🍜
👉Ref-NeRF: reflected radiance & structures via collection of spatially-varying scene properties
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Realism and accuracy
✅Replacing NeRF’s params
✅Regularization of volume density
✅Integrated Directional Encoding
More: https://bit.ly/3tTlS5l
👉Ref-NeRF: reflected radiance & structures via collection of spatially-varying scene properties
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Realism and accuracy
✅Replacing NeRF’s params
✅Regularization of volume density
✅Integrated Directional Encoding
More: https://bit.ly/3tTlS5l
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🦧OFA for all: Cross, Vision, Language🦧
👉Unified multimodal model for image generation, visual grounding, etc.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Sequence-to-sequence learning
✅Image Captioning / Generation
✅Visual Grounding / Classification
✅Text-to-Image Generation
✅Visual Question Answering
More: https://bit.ly/3wSTGlc
👉Unified multimodal model for image generation, visual grounding, etc.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Sequence-to-sequence learning
✅Image Captioning / Generation
✅Visual Grounding / Classification
✅Text-to-Image Generation
✅Visual Question Answering
More: https://bit.ly/3wSTGlc
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🍿Old Films Back to Life with #AI🍿
👉Recurrent transformer network (RTN) to restore heavily degraded old films
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Transformer blocks for spatial
✅Knowledge from adjacent frames
✅Color from keyframes to whole clip
✅Source code available in days!
More: https://bit.ly/3wZbV8y
👉Recurrent transformer network (RTN) to restore heavily degraded old films
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Transformer blocks for spatial
✅Knowledge from adjacent frames
✅Color from keyframes to whole clip
✅Source code available in days!
More: https://bit.ly/3wZbV8y
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🍊Neural Head #Avatars from RGB🍊
👉Novel neural representation for animatable head avatar
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel articulated human head
✅Full-geometry reconstruction
✅Differentiable optimization pipeline
✅Disentanglement of shape/color
More: https://bit.ly/3DxUGMI
👉Novel neural representation for animatable head avatar
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel articulated human head
✅Full-geometry reconstruction
✅Differentiable optimization pipeline
✅Disentanglement of shape/color
More: https://bit.ly/3DxUGMI
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🌶️ MyStyle: personal generative #AI 🌶️
👉Personalized deep generation with a few shots of a person
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Small set of portraits(∼100)
✅Local, low-dim, personal manifold
✅Personal #AI for ill-posed tasks
✅SOTA vs. previous few-shots
More: https://bit.ly/3wWMwMu
👉Personalized deep generation with a few shots of a person
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Small set of portraits(∼100)
✅Local, low-dim, personal manifold
✅Personal #AI for ill-posed tasks
✅SOTA vs. previous few-shots
More: https://bit.ly/3wWMwMu
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🦆 GAN + Dense Map 🦆
👉CoordGAN: structure-texture disentangled GAN with dense correspondence map
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel coordinate space
✅Warping to learn coordinate
✅Encoder for structure representation
✅HQ structure/texture editable images
More: https://bit.ly/3DOlOaB
👉CoordGAN: structure-texture disentangled GAN with dense correspondence map
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel coordinate space
✅Warping to learn coordinate
✅Encoder for structure representation
✅HQ structure/texture editable images
More: https://bit.ly/3DOlOaB
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