361 citations · 1.3k across the 81 of their papers we have counts for
97 papers · 1 filter
Forecasting the Number of Harvest-ready Fruits of Sweet Peppers Using Multimodal Time-Series Data
Enrico Pallotta, Mohamed Farag, Esra Guclu +3
Accurate yield forecasting at the individual-plant level is critical for precision agriculture and supply-chain planning, yet public datasets capturing both visual growth dynamics…
Still image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels
Michael Halstead, Esra Guclu, Mohamed Farag +7
In this manuscript we release two datasets for visual sensing of tomato plants grown in commercial-like settings and acquired using a robot. The first is BUTom21 which consists of…
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…
Location-aware Adaptive Normalization: A Deep Learning Approach For Wildfire Danger Forecasting
Mohamad Hakam Shams Eddin, Ribana Roscher, Juergen Gall
Climate change is expected to intensify and increase extreme events in the weather cycle. Since this has a significant impact on various sectors of our life, recent works are conce…
Robust Action Segmentation from Timestamp Supervision
Yaser Souri, Yazan Abu Farha, Emad Bahrami +2
Action segmentation is the task of predicting an action label for each frame of an untrimmed video. As obtaining annotations to train an approach for action segmentation in a fully…
Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation
Nadine Behrmann, S. Alireza Golestaneh, Zico Kolter +2
This paper introduces a unified framework for video action segmentation via sequence to sequence (seq2seq) translation in a fully and timestamp supervised setup. In contrast to cur…
Dual Pyramid Generative Adversarial Networks for Semantic Image Synthesis
Shijie Li, Ming-Ming Cheng, Juergen Gall
The goal of semantic image synthesis is to generate photo-realistic images from semantic label maps. It is highly relevant for tasks like content generation and image editing. Curr…
Self-supervised Learning for Unintentional Action Prediction
Olga Zatsarynna, Yazan Abu Farha, Juergen Gall
Distinguishing if an action is performed as intended or if an intended action fails is an important skill that not only humans have, but that is also important for intelligent syst…
One-Shot Synthesis of Images and Segmentation Masks
Vadim Sushko, Dan Zhang, Juergen Gall +1
Joint synthesis of images and segmentation masks with generative adversarial networks (GANs) is promising to reduce the effort needed for collecting image data with pixel-wise anno…
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…
Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives
David T. Hoffmann, Nadine Behrmann, Juergen Gall +2
This paper introduces Ranking Info Noise Contrastive Estimation (RINCE), a new member in the family of InfoNCE losses that preserves a ranked ordering of positive samples. In contr…
Keypoint Message Passing for Video-based Person Re-Identification
Di Chen, Andreas Doering, Shanshan Zhang +3
Video-based person re-identification (re-ID) is an important technique in visual surveillance systems which aims to match video snippets of people captured by different cameras. Ex…
Adaptive Token Sampling For Efficient Vision Transformers
Mohsen Fayyaz, Soroush Abbasi Koohpayegani, Farnoush Rezaei Jafari +5
While state-of-the-art vision transformer models achieve promising results in image classification, they are computationally expensive and require many GFLOPs. Although the GFLOPs…
TaylorSwiftNet: Taylor Driven Temporal Modeling for Swift Future Frame Prediction
Saber Pourheydari, Emad Bahrami, Mohsen Fayyaz +3
While recurrent neural networks (RNNs) demonstrate outstanding capabilities for future video frame prediction, they model dynamics in a discrete time space, i.e., they predict the…
Long Short View Feature Decomposition via Contrastive Video Representation Learning
Nadine Behrmann, Mohsen Fayyaz, Juergen Gall +1
Self-supervised video representation methods typically focus on the representation of temporal attributes in videos. However, the role of stationary versus non-stationary attribute…
FIFA: Fast Inference Approximation for Action Segmentation
Yaser Souri, Yazan Abu Farha, Fabien Despinoy +2
We introduce FIFA, a fast approximate inference method for action segmentation and alignment. Unlike previous approaches, FIFA does not rely on expensive dynamic programming for in…
Multi-Modal Temporal Convolutional Network for Anticipating Actions in Egocentric Videos
Olga Zatsarynna, Yazan Abu Farha, Juergen Gall
Anticipating human actions is an important task that needs to be addressed for the development of reliable intelligent agents, such as self-driving cars or robot assistants. While…
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…