TRACER: Extreme Attention Guided Salient Object Tracing Network (Student Abstract)
Keywords:Computer Vision, Segmentation, Salient Object Detection, Attention Mechanism, Adaptive Pixel Intensity
AbstractExisting studies on salient object detection (SOD) focus on extracting distinct objects with edge features and aggregating multi-level features to improve SOD performance. However, both performance gain and computational efficiency cannot be achieved, which has motivated us to study the inefficiencies in existing encoder-decoder structures to avoid this trade-off. We propose TRACER which excludes multi-decoder structures and minimizes the learning parameters usage by employing attention guided tracing modules (ATMs), as shown in Fig. 1.
How to Cite
Lee, M. S., Shin, W., & Han, S. W. (2022). TRACER: Extreme Attention Guided Salient Object Tracing Network (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12993-12994. https://doi.org/10.1609/aaai.v36i11.21633
AAAI Student Abstract and Poster Program