178 citations · 569 across the 193 of their papers we have counts for
24 papers · 1 filter
Beyond the Field-of-View: Enhancing Scene Visibility and Perception with Clip-Recurrent Transformer
Hao Shi, Qi Jiang, Kailun Yang +3
Vision sensors are widely applied in vehicles, robots, and roadside infrastructure. However, due to limitations in hardware cost and system size, camera Field-of-View (FoV) is ofte…
Computational Imaging for Machine Perception: Transferring Semantic Segmentation beyond Aberrations
Qi Jiang, Hao Shi, Shaohua Gao +5
Semantic scene understanding with Minimalist Optical Systems (MOS) in mobile and wearable applications remains a challenge due to the corrupted imaging quality induced by optical a…
LF-VISLAM: A SLAM Framework for Large Field-of-View Cameras with Negative Imaging Plane on Mobile Agents
Ze Wang, Kailun Yang, Hao Shi +4
Simultaneous Localization And Mapping (SLAM) has become a crucial aspect in the fields of autonomous driving and robotics. One crucial component of visual SLAM is the Field-of-View…
Multi-modal Depression Estimation based on Sub-attentional Fusion
Ping-Cheng Wei, Kunyu Peng, Alina Roitberg +3
Failure to timely diagnose and effectively treat depression leads to over 280 million people suffering from this psychological disorder worldwide. The information cues of depressio…
Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation
Jiaming Zhang, Kailun Yang, Hao Shi +7
In this paper, we address panoramic semantic segmentation which is under-explored due to two critical challenges: (1) image distortions and object deformations on panoramas; (2) la…
Trans4Map: Revisiting Holistic Bird's-Eye-View Mapping from Egocentric Images to Allocentric Semantics with Vision Transformers
Chang Chen, Jiaming Zhang, Kailun Yang +2
Humans have an innate ability to sense their surroundings, as they can extract the spatial representation from the egocentric perception and form an allocentric semantic map via sp…
Panoramic Panoptic Segmentation: Insights Into Surrounding Parsing for Mobile Agents via Unsupervised Contrastive Learning
Alexander Jaus, Kailun Yang, Rainer Stiefelhagen
In this work, we introduce panoramic panoptic segmentation, as the most holistic scene understanding, both in terms of Field of View (FoV) and image-level understanding for standar…
Annular Computational Imaging: Capture Clear Panoramic Images through Simple Lens
Qi Jiang, Hao Shi, Lei Sun +3
Panoramic Annular Lens (PAL) composed of few lenses has great potential in panoramic surrounding sensing tasks for mobile and wearable devices because of its tiny size and large Fi…
Efficient Human Pose Estimation via 3D Event Point Cloud
Jiaan Chen, Hao Shi, Yaozu Ye +3
Human Pose Estimation (HPE) based on RGB images has experienced a rapid development benefiting from deep learning. However, event-based HPE has not been fully studied, which remain…
Review on Panoramic Imaging and Its Applications in Scene Understanding
Shaohua Gao, Kailun Yang, Hao Shi +2
With the rapid development of high-speed communication and artificial intelligence technologies, human perception of real-world scenes is no longer limited to the use of small Fiel…
Towards Automatic Parsing of Structured Visual Content through the Use of Synthetic Data
Lukas Scholch, Jonas Steinhauser, Maximilian Beichter +6
Structured Visual Content (SVC) such as graphs, flow charts, or the like are used by authors to illustrate various concepts. While such depictions allow the average reader to bette…
Is my Driver Observation Model Overconfident? Input-guided Calibration Networks for Reliable and Interpretable Confidence Estimates
Alina Roitberg, Kunyu Peng, David Schneider +4
Driver observation models are rarely deployed under perfect conditions. In practice, illumination, camera placement and type differ from the ones present during training and unfore…
Indoor Navigation Assistance for Visually Impaired People via Dynamic SLAM and Panoptic Segmentation with an RGB-D Sensor
Wenyan Ou, Jiaming Zhang, Kunyu Peng +4
Exploring an unfamiliar indoor environment and avoiding obstacles is challenging for visually impaired people. Currently, several approaches achieve the avoidance of static obstacl…
Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-Learning
Xinyu Luo, Jiaming Zhang, Kailun Yang +3
Autonomous vehicles utilize urban scene segmentation to understand the real world like a human and react accordingly. Semantic segmentation of normal scenes has experienced a remar…
Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation
Jiaming Zhang, Kailun Yang, Chaoxiang Ma +3
Panoramic images with their 360-degree directional view encompass exhaustive information about the surrounding space, providing a rich foundation for scene understanding. To unfold…
MatchFormer: Interleaving Attention in Transformers for Feature Matching
Qing Wang, Jiaming Zhang, Kailun Yang +2
Local feature matching is a computationally intensive task at the subpixel level. While detector-based methods coupled with feature descriptors struggle in low-texture scenes, CNN-…
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
Jiaming Zhang, Huayao Liu, Kailun Yang +3
Scene understanding based on image segmentation is a crucial component of autonomous vehicles. Pixel-wise semantic segmentation of RGB images can be advanced by exploiting compleme…
TransDARC: Transformer-based Driver Activity Recognition with Latent Space Feature Calibration
Kunyu Peng, Alina Roitberg, Kailun Yang +2
Traditional video-based human activity recognition has experienced remarkable progress linked to the rise of deep learning, but this effect was slower as it comes to the downstream…
CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous Driving
Hao Shi, Yifan Zhou, Kailun Yang +2
Optical flow estimation is an essential task in self-driving systems, which helps autonomous vehicles perceive temporal continuity information of surrounding scenes. The calculatio…
TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation
Ruiping Liu, Kailun Yang, Alina Roitberg +5
Semantic segmentation benchmarks in the realm of autonomous driving are dominated by large pre-trained transformers, yet their widespread adoption is impeded by substantial computa…
PanoFlow: Learning 360° Optical Flow for Surrounding Temporal Understanding
Hao Shi, Yifan Zhou, Kailun Yang +7
Optical flow estimation is a basic task in self-driving and robotics systems, which enables to temporally interpret traffic scenes. Autonomous vehicles clearly benefit from the ult…
LF-VIO: A Visual-Inertial-Odometry Framework for Large Field-of-View Cameras with Negative Plane
Ze Wang, Kailun Yang, Hao Shi +3
Visual-inertial-odometry has attracted extensive attention in the field of autonomous driving and robotics. The size of Field of View (FoV) plays an important role in Visual-Odomet…
Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse Occlusions
Kunyu Peng, Alina Roitberg, Kailun Yang +2
Occlusions are universal disruptions constantly present in the real world. Especially for sparse representations, such as human skeletons, a few occluded points might destroy the g…
Should I take a walk? Estimating Energy Expenditure from Video Data
Kunyu Peng, Alina Roitberg, Kailun Yang +2
We explore the problem of automatically inferring the amount of kilocalories used by human during physical activity from his/her video observation. To study this underresearched ta…