no code implementations • 15 Sep 2023 • Tianxu Wu, Shuo Ye, Shuhuang Chen, Qinmu Peng, Xinge You
To address this issue, we propose a novel approach termed the detail reinforcement diffusion model~(DRDM), which leverages the rich knowledge of large models for fine-grained data augmentation and comprises two key components including discriminative semantic recombination (DSR) and spatial knowledge reference~(SKR).
no code implementations • 6 Sep 2023 • Sichao Fu, Qinmu Peng, Yang He, Baokun Du, Xinge You
In recent years, graph neural networks (GNN) have achieved significant developments in a variety of graph analytical tasks.
1 code implementation • 11 Apr 2023 • Conghao Wong, Beihao Xia, Qinmu Peng, Xinge You
In this paper, we bring a new ``view'' for trajectory prediction to model and forecast trajectories hierarchically according to different frequency portions from the spectral domain to learn to forecast trajectories by considering their frequency responses.
no code implementations • 27 Mar 2023 • Wenhao Qiu, Sichao Fu, Jingyi Zhang, Chengxiang Lei, Qinmu Peng
And then, a text encoder is introduced to automatically generate the corresponding semantic (text) labels for each image from the base classes.
Ranked #1 on Few-Shot Class-Incremental Learning on CUB-200-2011
no code implementations • 16 Feb 2023 • Chengxiang Lei, Sichao Fu, Yuetian Wang, Wenhao Qiu, Yachen Hu, Qinmu Peng, Xinge You
Some recent methods have been proposed to reconstruct the missing node features by the information propagation among nodes with known and unknown attributes.
no code implementations • 26 Sep 2022 • Yufeng Shi, Xinge You, Jiamiao Xu, Feng Zheng, Qinmu Peng, Weihua Ou
Hashing that projects data into binary codes has shown extraordinary talents in cross-modal retrieval due to its low storage usage and high query speed.
no code implementations • 6 May 2022 • Yufeng Shi, Shuhuang Chen, Xinge You, Qinmu Peng, Weihua Ou, Yue Zhao
Mapping X-ray images, radiology reports, and other medical data as binary codes in the common space, which can assist clinicians to retrieve pathology-related data from heterogeneous modalities (i. e., hashing-based cross-modal medical data retrieval), provides a new view to promot computeraided diagnosis.
2 code implementations • CVPR 2022 • Shiming Chen, Ziming Hong, Guo-Sen Xie, Wenhan Yang, Qinmu Peng, Kai Wang, Jian Zhao, Xinge You
Prior works either simply align the global features of an image with its associated class semantic vector or utilize unidirectional attention to learn the limited latent semantic representations, which could not effectively discover the intrinsic semantic knowledge e. g., attribute semantics) between visual and attribute features.
no code implementations • 17 Feb 2022 • Beihao Xia, Conghao Wong, Qinmu Peng, Wei Yuan, Xinge You
The current methods are dedicated to studying the agents' future trajectories under the social interaction and the sceneries' physical constraints.
1 code implementation • 3 Dec 2021 • Shiming Chen, Ziming Hong, Yang Liu, Guo-Sen Xie, Baigui Sun, Hao Li, Qinmu Peng, Ke Lu, Xinge You
Although some attention-based models have attempted to learn such region features in a single image, the transferability and discriminative attribute localization of visual features are typically neglected.
1 code implementation • 14 Oct 2021 • Conghao Wong, Beihao Xia, Ziming Hong, Qinmu Peng, Wei Yuan, Qiong Cao, Yibo Yang, Xinge You
Different frequency bands in the trajectory spectrums could hierarchically reflect agents' motion preferences at different scales.
Ranked #3 on Trajectory Prediction on ETH/UCY
2 code implementations • NeurIPS 2021 • Shiming Chen, Guo-Sen Xie, Yang Liu, Qinmu Peng, Baigui Sun, Hao Li, Xinge You, Ling Shao
Specifically, HSVA aligns the semantic and visual domains by adopting a hierarchical two-step adaptation, i. e., structure adaptation and distribution adaptation.
1 code implementation • ICCV 2021 • Shiming Chen, Wenjie Wang, Beihao Xia, Qinmu Peng, Xinge You, Feng Zheng, Ling Shao
FREE employs a feature refinement (FR) module that incorporates \textit{semantic$\rightarrow$visual} mapping into a unified generative model to refine the visual features of seen and unseen class samples.
1 code implementation • 2 Jul 2021 • Conghao Wong, Beihao Xia, Qinmu Peng, Wei Yuan, Xinge You
Then, we assume that the target agents may plan their future behaviors according to each of these categorized styles, thus utilizing different style channels to make predictions with significant style differences in parallel.
no code implementations • 8 Oct 2020 • Beihao Xia, Conghao Wong, Heng Li, Shiming Chen, Qinmu Peng, Xinge You
Visual images usually contain the informative context of the environment, thereby helping to predict agents' behaviors.
no code implementations • 22 Mar 2020 • Jiamiao Xu, Fangzhao Wang, Qinmu Peng, Xinge You, Shuo Wang, Xiao-Yuan Jing, C. L. Philip Chen
Furthermore, recent low-rank modeling provides a satisfactory solution to address data contaminated by predefined assumptions of noise distribution, such as Gaussian or Laplacian distribution.
no code implementations • 13 Mar 2020 • Beihao Xia, Conghao Wang, Qinmu Peng, Xinge You, DaCheng Tao
It remains challenging to automatically predict the multi-agent trajectory due to multiple interactions including agent to agent interaction and scene to agent interaction.
1 code implementation • 11 Nov 2019 • Shiming Chen, Peng Zhang, Guo-Sen Xie, Qinmu Peng, Zehong Cao, Wei Yuan, Xinge You
Dynamic texture (DT) exhibits statistical stationarity in the spatial domain and stochastic repetitiveness in the temporal dimension, indicating that different frames of DT possess a high similarity correlation that is critical prior knowledge.
no code implementations • 29 May 2019 • Zhengqiang Zhang, Shujian Yu, Shi Yin, Qinmu Peng, Xinge You
Weakly-supervised semantic segmentation aims to assign each pixel a semantic category under weak supervisions, such as image-level tags.
no code implementations • 21 Mar 2019 • Shi Yin, Zhengqiang Zhang, Qinmu Peng, Xinge You
High angular resolution diffusion imaging (HARDI) demands a lager amount of data measurements compared to diffusion tensor imaging, restricting its use in practice.
no code implementations • 5 Jan 2019 • Shi Yin, Zhengqiang Zhang, Hongming Li, Qinmu Peng, Xinge You, Susan L. Furth, Gregory E. Tasian, Yong Fan
It remains challenging to automatically segment kidneys in clinical ultrasound images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic methods have achieved promising performance.
no code implementations • 12 Nov 2018 • Shi Yin, Qinmu Peng, Hongming Li, Zhengqiang Zhang, Xinge You, Susan L. Furth, Gregory E. Tasian, Yong Fan
It remains challenging to automatically segment kidneys in clinical ultrasound (US) images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic methods have achieved promising performance.
no code implementations • 21 May 2018 • Qi Zheng, Shujian Yu, Xinge You, Qinmu Peng
Low-Rank Matrix Recovery (LRMR) has recently been applied to saliency detection by decomposing image features into a low-rank component associated with background and a sparse component associated with visual salient regions.