9 citations · 18 across the 11 of their papers we have counts for
11 papers
Tracing Generated Samples to Training-Data Clusters in Flow-Matching Models
Rania Briq, Ohad Fried, Michael Kamp +1
Understanding which training samples influence a generated image is an important problem in generative modeling. In flow matching, training samples influence the generated image th…
Exploring and Exploiting Stability in Latent Flow Matching
Rania Briq, Michael Kamp, Ohad Fried +2
In this work, we show that Latent Flow-Matching (LFM) models are robust to different types of perturbations, including data reduction and model capacity shrinkage. We characterize…
The Amazing Stability of Flow Matching
Rania Briq, Michael Kamp, Ohad Fried +2
The success of deep generative models in generating high-quality and diverse samples is often attributed to particular architectures and large training datasets. In this paper, we…
Lossy Neural Compression for Geospatial Analytics: A Review
Carlos Gomes, Isabelle Wittmann, Damien Robert +24
Over the past decades, there has been an explosion in the amount of available Earth Observation (EO) data. The unprecedented coverage of the Earth's surface and atmosphere by satel…
Scaling Image Tokenizers with Grouped Spherical Quantization
Jiangtao Wang, Zhen Qin, Yifan Zhang +4
Vision tokenizers have gained a lot of attraction due to their scalability and compactness; previous works depend on old-school GAN-based hyperparameters, biased comparisons, and a…
Data Pruning in Generative Diffusion Models
Rania Briq, Jiangtao Wang, Stefan Kesselheim
Data pruning is the problem of identifying a core subset that is most beneficial to training and discarding the remainder. While pruning strategies are well studied for discriminat…
Recurrent Transformer Variational Autoencoders for Multi-Action Motion Synthesis
Rania Briq, Chuhang Zou, Leonid Pishchulin +2
We consider the problem of synthesizing multi-action human motion sequences of arbitrary lengths. Existing approaches have mastered motion sequence generation in single action scen…
Towards Better Adversarial Synthesis of Human Images from Text
Rania Briq, Pratika Kochar, Juergen Gall
This paper proposes an approach that generates multiple 3D human meshes from text. The human shapes are represented by 3D meshes based on the SMPL model. The model's performance is…
Adversarial Synthesis of Human Pose from Text
Yifei Zhang, Rania Briq, Julian Tanke +1
This work focuses on synthesizing human poses from human-level text descriptions. We propose a model that is based on a conditional generative adversarial network. It is designed t…
Unifying Part Detection and Association for Recurrent Multi-Person Pose Estimation
Rania Briq, Andreas Doering, Juergen Gall
We propose a joint model of human joint detection and association for 2D multi-person pose estimation (MPPE). The approach unifies training of joint detection and association witho…
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation
Rania Briq, Michael Moeller, Juergen Gall
Weakly supervised semantic segmentation has been a subject of increased interest due to the scarcity of fully annotated images. We introduce a new approach for solving weakly super…