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Found 8 papers, 1 papers with code
SPAD : Spatially Aware Multiview Diffusers
We present SPAD, a novel approach for creating consistent multi-view images from text prompts or single images.
iNVS: Repurposing Diffusion Inpainters for Novel View Synthesis
Our approach focuses on maximizing the reuse of visible pixels from the source image.
Invertible Neural Skinning
Next, we combine PIN with a differentiable LBS module to build an expressive and end-to-end Invertible Neural Skinning (INS) pipeline.
Context-self contrastive pretraining for crop type semantic segmentation
For crop type semantic segmentation from Satellite Image Time Series (SITS) we find performance at parcel boundaries to be a critical bottleneck and explain how CSCL tackles the underlying cause of that problem, improving the state-of-the-art performance in this task.
HoloPose: Holistic 3D Human Reconstruction In-The-Wild
We introduce HoloPose, a method for holistic monocular 3D human body reconstruction.
Ranked #170 on
3D Human Pose Estimation
on Human3.6M
Lifting AutoEncoders: Unsupervised Learning of a Fully-Disentangled 3D Morphable Model using Deep Non-Rigid Structure from Motion
In this work we introduce Lifting Autoencoders, a generative 3D surface-based model of object categories.
Dense Pose Transfer
In this work we integrate ideas from surface-based modeling with neural synthesis: we propose a combination of surface-based pose estimation and deep generative models that allows us to perform accurate pose transfer, i. e. synthesize a new image of a person based on a single image of that person and the image of a pose donor.
DenseReg: Fully Convolutional Dense Shape Regression In-the-Wild
We define the regression task in terms of the intrinsic, U-V coordinates of a 3D deformable model that is brought into correspondence with image instances at training time.
