361 citations · 1.3k across the 81 of their papers we have counts for
7 papers · 1 filter
How Much Temporal Long-Term Context is Needed for Action Segmentation?
Emad Bahrami, Gianpiero Francesca, Juergen Gall
Modeling long-term context in videos is crucial for many fine-grained tasks including temporal action segmentation. An interesting question that is still open is how much long-term…
Semantic RGB-D Image Synthesis
Shijie Li, Rong Li, Juergen Gall
Collecting diverse sets of training images for RGB-D semantic image segmentation is not always possible. In particular, when robots need to operate in privacy-sensitive areas like…
Smoothness Similarity Regularization for Few-Shot GAN Adaptation
Vadim Sushko, Ruyu Wang, Juergen Gall
The task of few-shot GAN adaptation aims to adapt a pre-trained GAN model to a small dataset with very few training images. While existing methods perform well when the dataset for…
3DMOTFormer: Graph Transformer for Online 3D Multi-Object Tracking
Shuxiao Ding, Eike Rehder, Lukas Schneider +2
Tracking 3D objects accurately and consistently is crucial for autonomous vehicles, enabling more reliable downstream tasks such as trajectory prediction and motion planning. Based…
Action Anticipation with Goal Consistency
Olga Zatsarynna, Juergen Gall
In this paper, we address the problem of short-term action anticipation, i.e., we want to predict an upcoming action one second before it happens. We propose to harness high-level…
PowerBEV: A Powerful Yet Lightweight Framework for Instance Prediction in Bird's-Eye View
Peizheng Li, Shuxiao Ding, Xieyuanli Chen +3
Accurately perceiving instances and predicting their future motion are key tasks for autonomous vehicles, enabling them to navigate safely in complex urban traffic. While bird's-ey…
A Gated Attention Transformer for Multi-Person Pose Tracking
Andreas Doering, Juergen Gall
Multi-person pose tracking is an important element for many applications and requires to estimate the human poses of all persons in a video and to track them over time. The associa…