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Xin Zhan

7 accepted papers

2024

Construction of Paired Knowledge Graph - Text Datasets Informed by Cyclic Evaluation

COLING 2024main

Datasets that pair Knowledge Graphs (KG) and text together (KG-T) can be used to train forward and reverse neural models that generate text from KG and vice versa. However models trained on datasets where KG and text pairs are not equivalent can suffer from more hallucination and poorer recall. In t…

Cited by 2SourcePDFScholar
2023

PUPS: Point Cloud Unified Panoptic Segmentation

AAAI 2023technical

Point cloud panoptic segmentation is a challenging task that seeks a holistic solution for both semantic and instance segmentation to predict groupings of coherent points. Previous approaches treat semantic and instance segmentation as surrogate tasks, and they either use clustering methods or bound…

Cited by 25SourcePDFScholar
2022

BE-STI: Spatial-Temporal Integrated Network for Class-Agnostic Motion Prediction With Bidirectional Enhancement

CVPR 2022poster

Determining the motion behavior of inexhaustible categories of traffic participants is critical for autonomous driving. In recent years, there has been a rising concern in performing class-agnostic motion prediction directly from the captured sensor data, like LiDAR point clouds or the combination o…

Cited by 30PDFcodeScholar
2022

INT: Towards Infinite-Frames 3D Detection with an Efficient Framework

ECCV 2022poster

"It is natural to construct a multi-frame instead of a single-frame 3D detector for a continuous-time stream. Although increasing the number of frames might improve performance, previous multi-frame studies only used very limited frames to build their systems due to the dramatically increased comput…

2022

LIFT: Learning 4D LiDAR Image Fusion Transformer for 3D Object Detection

CVPR 2022poster

LiDAR and camera are two common sensors to collect data in time for 3D object detection under the autonomous driving context. Though the complementary information across sensors and time has great potential of benefiting 3D perception, taking full advantage of sequential cross-sensor data still rema…

Cited by 37PDFScholar
2022

SP-Net: Slowly Progressing Dynamic Inference Networks

ECCV 2022poster

"Dynamic inference networks improve computational efficiency by executing a subset of network components, i.e., executing path, conditioned on input sample. Prevalent methods typically assign routers to computational blocks so that a computational block can be skipped or executed. However, such infe…

2021

PVGNet: A Bottom-Up One-Stage 3D Object Detector With Integrated Multi-Level Features

CVPR 2021poster

Quantization-based methods are widely used in LiDAR points 3D object detection for its efficiency in extracting context information. Unlike image where the context information is distributed evenly over the object, most LiDAR points are distributed along the object boundary, which means the boundary…

Cited by 57PDFScholar