31 citations · 60 across the 16 of their papers we have counts for
14 papers · 1 filter
ClimateVID -- Social Media Videos Analysis and Challenges Involved
Shiqi Xu, Moritz Burmester, Katharina Prasse +3
The pervasive growth of digital content, specifically short videos on social media platforms, has significantly altered how topics are discussed and understood in public discourse.…
From Codebooks to VLMs: Evaluating Automated Visual Discourse Analysis for Climate Change on Social Media
Katharina Prasse, Steffen Jung, Isaac Bravo +4
Social media platforms have become primary arenas for climate communication, generating millions of images and posts that - if systematically analysed - can reveal which communicat…
VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis
Yumeng Li, William Beluch, Margret Keuper +2
Despite tremendous progress in the field of text-to-video (T2V) synthesis, open-sourced T2V diffusion models struggle to generate longer videos with dynamically varying and evolvin…
Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive
Yumeng Li, Margret Keuper, Dan Zhang +1
Despite the recent advances in large-scale diffusion models, little progress has been made on the layout-to-image (L2I) synthesis task. Current L2I models either suffer from poor e…
Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition
Katharina Prasse, Steffen Jung, Yuxuan Zhou +1
Hand action recognition is essential. Communication, human-robot interactions, and gesture control are dependent on it. Skeleton-based action recognition traditionally includes han…
Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain Generalization
Yumeng Li, Dan Zhang, Margret Keuper +1
The generalization with respect to domain shifts, as they frequently appear in applications such as autonomous driving, is one of the remaining big challenges for deep learning mod…
Divide & Bind Your Attention for Improved Generative Semantic Nursing
Yumeng Li, Margret Keuper, Dan Zhang +1
Emerging large-scale text-to-image generative models, e.g., Stable Diffusion (SD), have exhibited overwhelming results with high fidelity. Despite the magnificent progress, current…
Overcoming Topology Agnosticism: Enhancing Skeleton-Based Action Recognition through Redefined Skeletal Topology Awareness
Yuxuan Zhou, Zhi-Qi Cheng, Jun-Yan He +3
Graph Convolutional Networks (GCNs) have long defined the state-of-the-art in skeleton-based action recognition, leveraging their ability to unravel the complex dynamics of human j…
Hypergraph Transformer for Skeleton-based Action Recognition
Yuxuan Zhou, Zhi-Qi Cheng, Chao Li +4
Skeleton-based action recognition aims to recognize human actions given human joint coordinates with skeletal interconnections. By defining a graph with joints as vertices and thei…
Intra-Source Style Augmentation for Improved Domain Generalization
Yumeng Li, Dan Zhang, Margret Keuper +1
The generalization with respect to domain shifts, as they frequently appear in applications such as autonomous driving, is one of the remaining big challenges for deep learning mod…
SP-ViT: Learning 2D Spatial Priors for Vision Transformers
Yuxuan Zhou, Wangmeng Xiang, Chao Li +5
Recently, transformers have shown great potential in image classification and established state-of-the-art results on the ImageNet benchmark. However, compared to CNNs, transformer…
Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis
Yang He, Ning Yu, Margret Keuper +1
The rapid advances in deep generative models over the past years have led to highly {realistic media, known as deepfakes,} that are commonly indistinguishable from real to human ey…
Learning Dilation Factors for Semantic Segmentation of Street Scenes
Yang He, Margret Keuper, Bernt Schiele +1
Contextual information is crucial for semantic segmentation. However, finding the optimal trade-off between keeping desired fine details and at the same time providing sufficiently…
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling
Yang He, Wei-Chen Chiu, Margret Keuper +1
We propose a novel superpixel-based multi-view convolutional neural network for semantic image segmentation. The proposed network produces a high quality segmentation of a single i…