1 citations · 3 across the 10 of their papers we have counts for
7 papers · 1 filter
MetricDepth: Enhancing Monocular Depth Estimation with Deep Metric Learning
Chunpu Liu, Guanglei Yang, Wangmeng Zuo +1
Deep metric learning aims to learn features relying on the consistency or divergence of class labels. However, in monocular depth estimation, the absence of a natural definition of…
Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation
Guanglei Yang, Yongqiang Zhang, Wanlong Li +5
Convolutional Neural Networks (CNNs) have significantly impacted various computer vision tasks, however, they inherently struggle to model long-range dependencies explicitly due to…
Multi-Modality Driven LoRA for Adverse Condition Depth Estimation
Guanglei Yang, Rui Tian, Yongqiang Zhang +3
The autonomous driving community is increasingly focused on addressing corner case problems, particularly those related to ensuring driving safety under adverse conditions (e.g., n…
Unprejudiced Training Auxiliary Tasks Makes Primary Better: A Multi-Task Learning Perspective
Yuanze Li, Chun-Mei Feng, Qilong Wang +2
Human beings can leverage knowledge from relative tasks to improve learning on a primary task. Similarly, multi-task learning methods suggest using auxiliary tasks to enhance a neu…
MR-GDINO: Efficient Open-World Continual Object Detection
Bowen Dong, Zitong Huang, Guanglei Yang +2
Open-world (OW) recognition and detection models show strong zero- and few-shot adaptation abilities, inspiring their use as initializations in continual learning methods to improv…
LayerMatch: Do Pseudo-labels Benefit All Layers?
Chaoqi Liang, Guanglei Yang, Lifeng Qiao +4
Deep neural networks have achieved remarkable performance across various tasks when supplied with large-scale labeled data. However, the collection of labeled data can be time-cons…
ConSept: Continual Semantic Segmentation via Adapter-based Vision Transformer
Bowen Dong, Guanglei Yang, Wangmeng Zuo +1
In this paper, we delve into the realm of vision transformers for continual semantic segmentation, a problem that has not been sufficiently explored in previous literature. Empiric…