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Changjian Jiang

7 accepted papers

2026

ARTDECO: Toward High-Fidelity On-the-Fly Reconstruction with Hierarchical Gaussian Structure and Feed-Forward Guidance

ICLR 2026poster

On-the-fly 3D reconstruction from monocular image sequences is a long-standing challenge in computer vision, critical for applications such as real-to-sim, AR/VR, and robotics. Existing methods face a major tradeoff: per-scene optimization yields high fidelity but is computationally expensive, where…

Cited by 0SourcecodeScholar
2025

LI-GS: Gaussian Splatting With LiDAR Incorporated for Accurate Large-Scale Reconstruction

RA-L 2025

Large-scale 3D reconstruction is critical in the field of robotics, and the potential of 3D Gaussian Splatting (3DGS) for achieving accurate object-level reconstruction has been demonstrated. However, ensuring geometric accuracy in outdoor and unbounded scenes remains a significant challenge. This s

Cited by 32SourceScholar
2025

PanopticSplatting: End-to-End Panoptic Gaussian Splatting

IROS 2025

Open-vocabulary panoptic reconstruction is a challenging task for simultaneous scene reconstruction and understanding. Recently, methods have been proposed for 3D scene understanding based on Gaussian splatting. However, these methods are multi-staged, suffering from the accumulated errors and the d

Cited by 2SourceScholar
2025

RISED: Accurate and Efficient RGB-Colorized Mapping Using Image Selection and Point Cloud Densification

ICRA 2025

Recent advances in robotics have underscored the critical role of colorized point clouds in enhancing environmental perception accuracy. However, conventional multisensor fusion Simultaneous Localization and Mapping (SLAM) systems typically employ all available images indiscriminately for point clou

Cited by 1SourceScholar
2022

A Two Stage Adaptation Framework for Frame Detection via Prompt Learning

COLING 2022main

Framing is a communication strategy to bias discussion by selecting and emphasizing. Frame detection aims to automatically analyze framing strategy. Previous works on frame detection mainly focus on a single scenario or issue, ignoring the special characteristics of frame detection that new events e…

2021

Align Voting Behavior with Public Statements for Legislator Representation Learning

ACL 2021long

Ideology of legislators is typically estimated by ideal point models from historical records of votes. It represents legislators and legislation as points in a latent space and shows promising results for modeling voting behavior. However, it fails to capture more specific attitudes of legislators t…

2020

Joint Representation Learning of Legislator and Legislation for Roll Call Prediction

IJCAI 2020poster

In this paper, we explore to learn representations of legislation and legislator for the prediction of roll call results. The most popular approach for this topic is named the ideal point model that relies on historical voting information for representation learning of legislators. It largely ignore…