Search Results for author:
Found 10 papers, 6 papers with code
Are Vision Language Models Texture or Shape Biased and Can We Steer Them?
If text does indeed influence visual biases, this suggests that we may be able to steer visual biases not just through visual input but also through language: a hypothesis that we confirm through extensive experiments.
Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition
We propose a method specifically designed for hand action recognition which uses relative angular embeddings and local Spherical Harmonics to create novel hand representations.
Neural Architecture Design and Robustness: A Dataset
We evaluate all these networks on a range of common adversarial attacks and corruption types and introduce a database on neural architecture design and robustness evaluations.
Happy People -- Image Synthesis as Black-Box Optimization Problem in the Discrete Latent Space of Deep Generative Models
In recent years, optimization in the learned latent space of deep generative models has been successfully applied to black-box optimization problems such as drug design, image generation or neural architecture search.
CosPGD: a unified white-box adversarial attack for pixel-wise prediction tasks
Further, we set a new benchmark for adversarial attacks on optical flow, and image restoration displaying the ability to extend to any pixel-wise prediction task.
Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks
The minimum cost multicut problem is the NP-hard/APX-hard combinatorial optimization problem of partitioning a real-valued edge-weighted graph such as to minimize the total cost of the partition.
FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting
Over the last years, Convolutional Neural Networks (CNNs) have been the dominating neural architecture in a wide range of computer vision tasks.
Learning Where To Look -- Generative NAS is Surprisingly Efficient
the optimization of architectures for highest classification accuracy but also in the context of hardware constraints and outperform state-of-the-art methods on several NAS benchmarks for single and multiple objectives.
Optimizing Edge Detection for Image Segmentation with Multicut Penalties
The Minimum Cost Multicut Problem (MP) is a popular way for obtaining a graph decomposition by optimizing binary edge labels over edge costs.
Spectral Distribution Aware Image Generation
In this paper, we propose to generate images according to the frequency distribution of the real data by employing a spectral discriminator.
