Recent advances in detecting arbitrary objects in the real world are trained and evaluated
on object detection datasets with a relatively restricted vocabulary. To facilitate the …

In recent years, vision-centric Bird's Eye View (BEV) perception has garnered significant
interest from both industry and academia due to its inherent advantages, such as providing …

Very recently, Window-based Transformers, which computed self-attention within non-
overlapping local windows, demonstrated promising results on image classification …

Transformer 所具备的长距离建模能力和并行计算能力使其在自然语言处理领域取得了巨大
成功并逐步拓展至计算机视觉等领域. 本文以分类任务为切入, 介绍了典型视觉Transformer …

This paper presents ClusterFormer, a universal vision model that is based on the Clustering
paradigm with TransFormer. It comprises two novel designs: 1) recurrent cross-attention …

The past few years have witnessed the immense success of object detection, while current
excellent detectors struggle on tackling size-limited instances. Concretely, the well-known …

Detection Transformer (DETR) and Deformable DETR have been proposed to eliminate the
need for many hand-designed components in object detection while demonstrating good …

Human-centric perceptions (eg, pose estimation, human parsing, pedestrian detection,
person re-identification, etc.) play a key role in industrial applications of visual models. While …

Forecasting future trajectories of agents in complex traffic scenes requires reliable and
efficient predictions for all agents in the scene. However, existing methods for trajectory …

Visual segmentation seeks to partition images, video frames, or point clouds into multiple
segments or groups. This technique has numerous real-world applications, such as …