Typical layout-to-image synthesis (LIS) models generate images for a closed set of semantic
classes, eg, 182 common objects in COCO-Stuff. In this work, we explore the freestyle …

Denoising Diffusion Probabilistic Models (DDPMs) have achieved remarkable success in
various image generation tasks compared with Generative Adversarial Nets (GANs). Recent …

Current semantic segmentation methods mainly focus on modeling the context of the global
image to obtain high-quality segmentation results. However, they ignore the role of local …

The traditional complete dual-branch structure is effective for semantic segmentation tasks.
However, it is redundant in some sense. Moreover, the simple additive fusion of the features …

Advances in both lossy image compression and semantic content understanding have been
greatly fueled by deep learning techniques, yet these two tasks have been developed …

We propose an efficient plug-and-play acceleration framework for semi-supervised video
object segmentation by exploiting the temporal redundancies in videos presented by the …

In this paper, we propose a separable structure modeling approach for semi-supervised
video object segmentation. Unlike most existing methods which preclude the semantically …

Human pose estimation from videos has many real-world applications. Existing methods
focus on applying models with a uniform computation profile on fully de-coded frames …

Enhancing the accuracy of dense classification with limited labeled data and abundant
unlabeled data, known as semi-supervised semantic segmentation, is an essential task in …

Compared with 2D image salient object detection (SOD), SOD in omnidirectional images (or
360° images) usually suffers from geometric distortion. Although existing omnidirectional …