50 citations · 199 across the 13 of their papers we have counts for
13 papers
Evolving Without Ending: Unifying Multimodal Incremental Learning for Continual Panoptic Perception
Bo Yuan, Danpei Zhao, Wentao Li +2
Continual learning (CL) is a great endeavour in developing intelligent perception AI systems. However, the pioneer research has predominantly focus on single-task CL, which restric…
Dual-Stream Spectral Decoupling Distillation for Remote Sensing Object Detection
Xiangyi Gao, Danpei Zhao, Bo Yuan +1
Knowledge distillation is an effective and hardware-friendly method, which plays a key role in lightweighting remote sensing object detection. However, existing distillation method…
Reconciling Semantic Controllability and Diversity for Remote Sensing Image Synthesis with Hybrid Semantic Embedding
Junde Liu, Danpei Zhao, Bo Yuan +2
Significant advancements have been made in semantic image synthesis in remote sensing. However, existing methods still face formidable challenges in balancing semantic controllabil…
RescueADI: Adaptive Disaster Interpretation in Remote Sensing Images with Autonomous Agents
Zhuoran Liu, Danpei Zhao, Bo Yuan
Current methods for disaster scene interpretation in remote sensing images (RSIs) mostly focus on isolated tasks such as segmentation, detection, or visual question-answering (VQA)…
TopoNAS: Boosting Search Efficiency of Gradient-based NAS via Topological Simplification
Danpei Zhao, Zhuoran Liu, Bo Yuan
Improving search efficiency serves as one of the crucial objectives of Neural Architecture Search (NAS). However, many current approaches ignore the universality of the search stra…
Continual Panoptic Perception: Towards Multi-modal Incremental Interpretation of Remote Sensing Images
Bo Yuan, Danpei Zhao, Zhuoran Liu +2
Continual learning (CL) breaks off the one-way training manner and enables a model to adapt to new data, semantics and tasks continuously. However, current CL methods mainly focus…
Learning at a Glance: Towards Interpretable Data-limited Continual Semantic Segmentation via Semantic-Invariance Modelling
Bo Yuan, Danpei Zhao, Zhenwei Shi
Continual semantic segmentation (CSS) based on incremental learning (IL) is a great endeavour in developing human-like segmentation models. However, current CSS approaches encounte…
Panoptic Perception: A Novel Task and Fine-grained Dataset for Universal Remote Sensing Image Interpretation
Danpei Zhao, Bo Yuan, Ziqiang Chen +4
Current remote-sensing interpretation models often focus on a single task such as detection, segmentation, or caption. However, the task-specific designed models are unattainable t…
PETDet: Proposal Enhancement for Two-Stage Fine-Grained Object Detection
Wentao Li, Danpei Zhao, Bo Yuan +2
Fine-grained object detection (FGOD) extends object detection with the capability of fine-grained recognition. In recent two-stage FGOD methods, the region proposal serves as a cru…
A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and Application
Bo Yuan, Danpei Zhao
Continual learning, also known as incremental learning or life-long learning, stands at the forefront of deep learning and AI systems. It breaks through the obstacle of one-way tra…
Inherit with Distillation and Evolve with Contrast: Exploring Class Incremental Semantic Segmentation Without Exemplar Memory
Danpei Zhao, Bo Yuan, Zhenwei Shi
As a front-burner problem in incremental learning, class incremental semantic segmentation (CISS) is plagued by catastrophic forgetting and semantic drift. Although recent methods…
Birds of A Feather Flock Together: Category-Divergence Guidance for Domain Adaptive Segmentation
Bo Yuan, Danpei Zhao, Shuai Shao +2
Unsupervised domain adaptation (UDA) aims to enhance the generalization capability of a certain model from a source domain to a target domain. Present UDA models focus on alleviati…
Focal and Global Knowledge Distillation for Detectors
Zhendong Yang, Zhe Li, Xiaohu Jiang +4
Knowledge distillation has been applied to image classification successfully. However, object detection is much more sophisticated and most knowledge distillation methods have fail…