6 accepted papers
Goal-directed scanpath prediction aims to predict people’s gaze shift path when searching for objects in a visual scene. Most existing goal-directed scanpath prediction methods cannot generalize to target classes not present during training. Besides, they usually exploit different pre-trained models…
Domain Adaptive Person Search (DAPS) aims to improve the generalization capability of person search models by training on both labeled source data and unlabeled target data, which is not that practical in real-world applications considering the storage/transmission costs and the privacy of source da…
Cross-Domain Few-shot Semantic Segmentation (CD-FSS) aims to train generalized models that can segment classes from different domains with a few labeled images. Previous works have proven the effectiveness of feature transformation in addressing CD-FSS. However, they completely rely on support image…
"Scanpath prediction in 360° images can help realize rapid rendering and better user interaction in Virtual/Augmented Reality applications. However, existing scanpath prediction models for 360° images execute scanpath prediction on 2D equirectangular projection plane, which always result in big comp…
Person search (PS) aims to jointly localize and identify a query person from natural, uncropped images. Existing works unintentionally adopt pedestrians (with similar poses and unchanging clothing) as the query and restrict the application scenarios in surveillance. This is due to that most PS datas…
Aiming at automatically discovering the common objects contained in a set of relevant images and segmenting them as foreground simultaneously, object co-segmentation has become an active research topic in recent years. Although a number of approaches have been proposed to address this problem, many…