The contextual information plays a core role in semantic segmentation. As for video
semantic segmentation, the contexts include static contexts and motional contexts …

Recent leading zero-shot video object segmentation (ZVOS) works devote to integrating
appearance and motion information by elaborately designing feature fusion modules and …

Robust and reliable semantic segmentation in complex scenes is crucial for many real-life
applications such as autonomous safe driving and nighttime rescue. In most approaches, it …

Video depth estimation aims to infer temporally consistent depth. Some methods achieve
temporal consistency by finetuning a single-image depth model during test time using …

The essence of video semantic segmentation (VSS) is how to leverage temporal information
for prediction. Previous efforts are mainly devoted to developing new techniques to calculate …

Abstract Video Semantic Segmentation (VSS) involves assigning a semantic label to each
pixel in a video sequence. Prior work in this field has demonstrated promising results by …

We present RAFTformer, a real-time action forecasting transformer for latency aware real-
world action forecasting applications. RAFTformer is a two-stage fully transformer based …

Since light field simultaneously records spatial information and angular information of light
rays, it is considered to be beneficial for many potential applications, and semantic …

The estimation of implicit cross-frame correspondences and the high computational cost
have long been major challenges in video semantic segmentation (VSS) for driving scenes …

In recent years, video semantic segmentation has made great progress with advanced deep
neural networks. However, there still exist two main challenges ie, information inconsistency …