2 code implementations • 9 Apr 2024 • Yanan Zhang, Xiaoling Bai, Tianhua Zhou
Furthermore, to strengthen the focus on critical event information in events, we include a decoder module after the document encoder, introduce a generative event triplet extraction scheme based on prompt-tuning, and correlate the events with query encoder optimization through comparative learning.
no code implementations • 23 Jan 2024 • Shun Fang, Ming Cui, Xing Feng, Yanan Zhang
NeRF's high-quality scene synthesis capability was quickly accepted by scholars in the years after it was proposed, and significant progress has been made in 3D scene representation and synthesis.
no code implementations • 17 Nov 2023 • Yongchao Feng, Shiwei Li, Yingjie Gao, Ziyue Huang, Yanan Zhang, Qingjie Liu, Yunhong Wang
Though feature-alignment based Domain Adaptive Object Detection (DAOD) have achieved remarkable progress, they ignore the source bias issue, i. e. the aligned features are more favorable towards the source domain, leading to a sub-optimal adaptation.
1 code implementation • ICCV 2023 • Jinqing Zhang, Yanan Zhang, Qingjie Liu, Yunhong Wang
In this paper, we propose Semantic-Aware BEV Pooling (SA-BEVPool), which can filter out background information according to the semantic segmentation of image features and transform image features into semantic-aware BEV features.
Ranked #9 on 3D Object Detection on nuScenes Camera Only
no code implementations • 30 May 2023 • Yanan Zhang, Weijie Cui, Yangfan Zhang, Xiaoling Bai, Zhe Zhang, Jin Ma, Xiang Chen, Tianhua Zhou
In search engines, query expansion (QE) is a crucial technique to improve search experience.
no code implementations • CVPR 2023 • Chao Zhou, Yanan Zhang, Jiaxin Chen, Di Huang
A key challenge for LiDAR-based 3D object detection is to capture sufficient features from large scale 3D scenes especially for distant or/and occluded objects.
no code implementations • 2 Nov 2022 • Haolin Deng, Yanan Zhang, Yangfan Zhang, Wangyang Ying, Changlong Yu, Jun Gao, Wei Wang, Xiaoling Bai, Nan Yang, Jin Ma, Xiang Chen, Tianhua Zhou
To the best of our knowledge, it is currently the largest manually-annotated Chinese dataset for open event extraction.
2 code implementations • 16 Sep 2022 • Jiangmeng Li, Wenwen Qiang, Yanan Zhang, Wenyi Mo, Changwen Zheng, Bing Su, Hui Xiong
As a successful approach to self-supervised learning, contrastive learning aims to learn invariant information shared among distortions of the input sample.
1 code implementation • 26 Aug 2022 • Jiangmeng Li, Yanan Zhang, Wenwen Qiang, Lingyu Si, Chengbo Jiao, Xiaohui Hu, Changwen Zheng, Fuchun Sun
To understand the reasons behind this phenomenon, we revisit the learning paradigm of knowledge distillation on the few-shot object detection task from the causal theoretic standpoint, and accordingly, develop a Structural Causal Model.
no code implementations • CVPR 2022 • Yanan Zhang, Jiaxin Chen, Di Huang
In autonomous driving, LiDAR point-clouds and RGB images are two major data modalities with complementary cues for 3D object detection.
no code implementations • 29 Sep 2021 • Qibin Li, Nianmin Yao, Jian Zhao, Yanan Zhang
Based on the traditional attention mechanism, multi-scale fusion self attention extracts phrase information at different scales by setting convolution kernels at different levels, and calculates the corresponding attention matrix at different scales, so that the model can better extract phrase level information.
no code implementations • 17 Sep 2021 • Zheng Lian, Yanan Zhang, Haichang Li, Rui Wang, Xiaohui Hu
The conventional encoder-decoder framework for image captioning generally adopts a single-pass decoding process, which predicts the target descriptive sentence word by word in temporal order.
no code implementations • 18 Dec 2020 • Yanan Zhang, Di Huang, Yunhong Wang
LiDAR-based 3D object detection is an important task for autonomous driving and current approaches suffer from sparse and partial point clouds of distant and occluded objects.
Ranked #4 on 3D Object Detection on KITTI Cars Hard val