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Found 9 papers, 3 papers with code
Towards Realistic 3D Embedding via View Alignment
Recent advances in generative adversarial networks (GANs) have achieved great success in automated image composition that generates new images by embedding interested foreground objects into background images automatically.
Adversarial Image Composition with Auxiliary Illumination
State-of-the-art methods strive to harmonize the composed image by adapting the style of foreground objects to be compatible with the background image, whereas the potential shadow of foreground objects within the composed image which is critical to the composition realism is largely neglected.
EMLight: Lighting Estimation via Spherical Distribution Approximation
Motivated by the Earth Mover distance, we design a novel spherical mover's loss that guides to regress light distribution parameters accurately by taking advantage of the subtleties of spherical distribution.
GMLight: Lighting Estimation via Geometric Distribution Approximation
This paper presents Geometric Mover's Light (GMLight), a lighting estimation framework that employs a regression network and a generative projector for effective illumination estimation.
Diverse Image Inpainting with Bidirectional and Autoregressive Transformers
With image-level attention, transformers enable to model long-range dependencies and generate diverse contents with autoregressive modeling of pixel-sequence distributions.
SA-ConvONet: Sign-Agnostic Optimization of Convolutional Occupancy Networks
To this end, we propose to learn implicit surface reconstruction by sign-agnostic optimization of convolutional occupancy networks, to simultaneously achieve advanced scalability to large-scale scenes, generality to novel shapes, and applicability to raw scans in a unified framework.
Unbalanced Feature Transport for Exemplar-based Image Translation
In addition, we design a semantic-activation normalization scheme that injects style features of exemplars into the image translation process successfully.
Sparse Needlets for Lighting Estimation with Spherical Transport Loss
Accurate lighting estimation is challenging yet critical to many computer vision and computer graphics tasks such as high-dynamic-range (HDR) relighting.
WaveFill: A Wavelet-based Generation Network for Image Inpainting
This paper presents WaveFill, a wavelet-based inpainting network that decomposes images into multiple frequency bands and fills the missing regions in each frequency band separately and explicitly.
