Search Results for author:
Found 8 papers, 2 papers with code
BodyMetric: Evaluating the Realism of Human Bodies in Text-to-Image Generation
In particular, we use BodyMetric to benchmark the generation ability of text-to-image models to produce realistic human bodies.
A Simple Strategy for Body Estimation from Partial-View Images
Virtual try-on and product personalization have become increasingly important in modern online shopping, highlighting the need for accurate body measurement estimation.
MRC-Net: 6-DoF Pose Estimation with MultiScale Residual Correlation
Connecting the two stages is a novel multi-scale residual correlation (MRC) layer that captures high-and-low level correspondences between the input image and rendering from first stage.
Human Body Measurement Estimation with Adversarial Augmentation
Training of BMnet is performed on data from real human subjects, and augmented with a novel adversarial body simulator (ABS) that finds and synthesizes challenging body shapes.
STRIVE: Scene Text Replacement In Videos
Finally, the new text is transferred from the reference to remaining frames using a novel learned image transformation network that captures lighting and blur effects in a temporally consistent manner.
LiDAM: Semi-Supervised Learning with Localized Domain Adaptation and Iterative Matching
Although data is abundant, data labeling is expensive.
Editing in Style: Uncovering the Local Semantics of GANs
Focusing on StyleGAN, we introduce a simple and effective method for making local, semantically-aware edits to a target output image.
Semi-supervised Conditional GANs
We introduce a new model for building conditional generative models in a semi-supervised setting to conditionally generate data given attributes by adapting the GAN framework.
