David Jacobs

papers

1,138

total citations

papers (14)

SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation

CVPR 2020arXiv

citations

Low Curvature Activations Reduce Overfitting in Adversarial Training

ICCV 2021arXiv

citations

HaLP: Hallucinating Latent Positives for Skeleton-Based Self-Supervised Learning of Actions

CVPR 2023arXiv

citations

LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation

ICCV 2023arXiv

citations

Shift Invariance Can Reduce Adversarial Robustness

NEURIPS 2021arXiv

citations

On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels

NEURIPS 2022arXiv

citations

Magic Insert: Style-Aware Drag-and-Drop

ICCV 2025arXiv

citations

Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach

NEURIPS 2023arXiv

citations

David Jacobs

papers (14)

Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models

Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer

On the Similarity between the Laplace and Neural Tangent Kernels

Robust Contrastive Learning Using Negative Samples with Diminished Semantics

Hyperbolic Contrastive Learning for Visual Representations Beyond Objects

Autoregressive Perturbations for Data Poisoning

SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation

Low Curvature Activations Reduce Overfitting in Adversarial Training

HaLP: Hallucinating Latent Positives for Skeleton-Based Self-Supervised Learning of Actions

LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation

Shift Invariance Can Reduce Adversarial Robustness

On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels

Magic Insert: Style-Aware Drag-and-Drop

Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach

papers (14)

Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models

Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer

On the Similarity between the Laplace and Neural Tangent Kernels

Robust Contrastive Learning Using Negative Samples with Diminished Semantics

Hyperbolic Contrastive Learning for Visual Representations Beyond Objects

Autoregressive Perturbations for Data Poisoning

SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation

Low Curvature Activations Reduce Overfitting in Adversarial Training

HaLP: Hallucinating Latent Positives for Skeleton-Based Self-Supervised Learning of Actions

LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation

Shift Invariance Can Reduce Adversarial Robustness

On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels

Magic Insert: Style-Aware Drag-and-Drop

Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach