no code implementations • 5 Apr 2024 • Chenyang Wu, Yifan Duan, Xinran Zhang, Yu Sheng, Jianmin Ji, Yanyong Zhang
In this work, we present MM-Gaussian, a LiDAR-camera multi-modal fusion system for localization and mapping in unbounded scenes.
2 code implementations • 14 Aug 2023 • Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai, Woosung Choi, Marco Martínez-Ramírez, WeiHsiang Liao, Igor Gadelha, Geraldo Ramos, Eddie Hsu, Hugo Rodrigues, Fabian-Robert Stöter, Alexandre Défossez, Yi Luo, Jianwei Yu, Dipam Chakraborty, Sharada Mohanty, Roman Solovyev, Alexander Stempkovskiy, Tatiana Habruseva, Nabarun Goswami, Tatsuya Harada, Minseok Kim, Jun Hyung Lee, Yuanliang Dong, Xinran Zhang, Jiafeng Liu, Yuki Mitsufuji
We propose a formalization of the errors that can occur in the design of a training dataset for MSS systems and introduce two new datasets that simulate such errors: SDXDB23_LabelNoise and SDXDB23_Bleeding.
no code implementations • 4 Apr 2023 • ZiMing Wang, Yujiang Liu, Yifan Duan, Xingchen Li, Xinran Zhang, Jianmin Ji, Erbao Dong, Yanyong Zhang
In this paper, we present the USTC FLICAR Dataset, which is dedicated to the development of simultaneous localization and mapping and precise 3D reconstruction of the workspace for heavy-duty autonomous aerial work robots.
1 code implementation • 10 May 2022 • Jiafeng Liu, Yuanliang Dong, Zehua Cheng, Xinran Zhang, Xiaobing Li, Feng Yu, Maosong Sun
In this work, we propose a permutation invariant language model, SymphonyNet, as a solution for symbolic symphony music generation.
Ranked #1 on Audio Generation on Symphony music
no code implementations • 9 Nov 2021 • Ziyi Liu, JiaQi Zhang, Yongshuai Hou, Xinran Zhang, Ge Li, Yang Xiang
Background: Electronic Health Records (EHRs) contain rich information of patients' health history, which usually include both structured and unstructured data.
no code implementations • 27 Aug 2021 • Xinran Zhang, Maosong Sun, Jiafeng Liu, Xiaobing Li
We propose nucleus sampling with randomized head (NS-RH) algorithm, which randomizes the high frequency part ("head") of the predicted distribution, in order to emphasize on the "comparatively low frequency" words.
no code implementations • 13 Mar 2021 • Xinran Zhang, Maosong Sun, Jiafeng Liu, Xiaobing Li
In natural language processing (NLP), the semantic similarity task requires large-scale, high-quality human-annotated labels for fine-tuning or evaluation.
no code implementations • 13 Mar 2021 • Xinran Zhang, Maosong Sun, Jiafeng Liu, Xiaobing Li
Traditional stochastic sampling methods only focus on truncating the unreliable "tail" of the distribution, and do not address the "head" part, which we show might contain tedious or even repetitive candidates with high probability that lead to repetition loops.
no code implementations • 5 Sep 2018 • Ke Wang, Han Song, Jiahui Zhang, Xinran Zhang, Hongen Liao
In this paper, we proposed a method which can fuse different modalities 3D data to get a large-scale and dense point cloud.