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Found 7 papers, 2 papers with code
DreamBeast: Distilling 3D Fantastical Animals with Part-Aware Knowledge Transfer
Existing SDS methods often struggle with this generation task due to a limited understanding of part-level semantics in text-to-image diffusion models.
Differentiable Neural Surface Refinement for Modeling Transparent Objects
Neural implicit surface reconstruction leveraging volume rendering has led to significant advances in multi-view reconstruction.
3D-GPT: Procedural 3D Modeling with Large Language Models
Our work highlights the potential of LLMs in 3D modeling, offering a basic framework for future advancements in scene generation and animation.
NeRFEditor: Differentiable Style Decomposition for Full 3D Scene Editing
Specifically, we use a NeRF model to generate numerous image-angle pairs to train an adjustor, which can adjust the StyleGAN latent code to generate high-fidelity stylized images for any given angle.
Harmonizer: Learning to Perform White-Box Image and Video Harmonization
Unlike prior methods that are based on black-box autoencoders, Harmonizer contains a neural network for filter argument prediction and several white-box filters (based on the predicted arguments) for image harmonization.
Ranked #7 on
Image Harmonization
on iHarmony4
Blind Image Decomposition
We propose and study a novel task named Blind Image Decomposition (BID), which requires separating a superimposed image into constituent underlying images in a blind setting, that is, both the source components involved in mixing as well as the mixing mechanism are unknown.
Defocus Blur Detection via Salient Region Detection Prior
Defocus blur Detection aims to separate the out-of-focus and depth-of-field areas in photos, which is an important work in computer vision.
