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Huaxia Xia

7 accepted papers

2022

3D-SPS: Single-Stage 3D Visual Grounding via Referred Point Progressive Selection

CVPR 2022oral

3D visual grounding aims to locate the referred target object in 3D point cloud scenes according to a free-form language description. Previous methods mostly follow a two-stage paradigm, i.e., language-irrelevant detection and cross-modal matching, which is limited by the isolated architecture. In s…

Cited by 69PDFcodeScholar
2021

End-to-End Video Instance Segmentation With Transformers

CVPR 2021poster

Video instance segmentation (VIS) is the task that requires simultaneously classifying, segmenting and tracking object instances of interest in video. Recent methods typically develop sophisticated pipelines to tackle this task. Here, we propose a new video instance segmentation framework built upon…

Cited by 854PDFcodeScholar
2021

Star Topology based Interaction for Robust Trajectory Forecasting in Dynamic Scene

ICRA 2021poster

Motion prediction of multiple agents in a dynamic scene is a crucial component in many real applications, including intelligent monitoring and autonomous driving. Due to the complex interactions among the agents and their interactions with the surrounding scene, accurate trajectory prediction is sti…

Cited by 3SourceScholar
2021

Tra2Tra: Trajectory-to-Trajectory Prediction With a Global Social Spatial-Temporal Attentive Neural Network

RA-L 2021

Accurate trajectory prediction plays a key role in robot navigation. It is beneficial for planning a collision-free and appropriate path for the autonomous robots, especially in crowded scenes. However, it is a particularly challenging task because there are complex and subtle interactions among ped

Cited by 42SourceScholar
2021

Twins: Revisiting the Design of Spatial Attention in Vision Transformers

NeurIPS 2021poster

Very recently, a variety of vision transformer architectures for dense prediction tasks have been proposed and they show that the design of spatial attention is critical to their success in these tasks. In this work, we revisit the design of the spatial attention and demonstrate that a carefully dev…

2019

StarNet: Pedestrian Trajectory Prediction using Deep Neural Network in Star Topology

IROS 2019poster

Pedestrian trajectory prediction is crucial for many important applications. This problem is a great challenge because of complicated interactions among pedestrians. Previous methods model only the pairwise interactions between pedestrians, which not only oversimplifies the interactions among pedest…

Cited by 100SourceScholar