Search Results for author: Beihao Xia

Found 13 papers, 7 papers with code

SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction

1 code implementation9 Oct 2023 Conghao Wong, Beihao Xia, Xinge You

Analyzing and forecasting trajectories of agents like pedestrians and cars in complex scenes has become more and more significant in many intelligent systems and applications.

Pedestrian Trajectory Prediction Trajectory Prediction

Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios

no code implementations14 Jun 2023 Hong Sun, Ziqiang Li, Pengfei Xia, Heng Li, Beihao Xia, Yi Wu, Bin Li

However, existing backdoor attack methods make unrealistic assumptions, assuming that all training data comes from a single source and that attackers have full access to the training data.

Backdoor Attack

Another Vertical View: A Hierarchical Network for Heterogeneous Trajectory Prediction via Spectrums

1 code implementation11 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.

Trajectory Prediction

TODE-Trans: Transparent Object Depth Estimation with Transformer

1 code implementation18 Sep 2022 Kang Chen, Shaochen Wang, Beihao Xia, Dongxu Li, Zhen Kan, Bin Li

We observe that the global characteristics of the transformer make it easier to extract contextual information to perform depth estimation of transparent areas.

Depth Estimation Object +2

A Comprehensive Survey on Data-Efficient GANs in Image Generation

no code implementations18 Apr 2022 Ziqiang Li, Beihao Xia, Jing Zhang, Chaoyue Wang, Bin Li

Generative Adversarial Networks (GANs) have achieved remarkable achievements in image synthesis.

Image Generation

CSCNet: Contextual Semantic Consistency Network for Trajectory Prediction in Crowded Spaces

no code implementations17 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.

Autonomous Driving Trajectory Prediction

FREE: Feature Refinement for Generalized Zero-Shot Learning

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.

Generalized Zero-Shot Learning

MSN: Multi-Style Network for Trajectory Prediction

1 code implementation2 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.

Robot Navigation Self-Driving Cars +1

BGM: Building a Dynamic Guidance Map without Visual Images for Trajectory Prediction

no code implementations8 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.

Trajectory Prediction

CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network

1 code implementation21 Aug 2020 Shiming Chen, Wenjie Wang, Beihao Xia, Xinge You, Zehong Cao, Weiping Ding

In essence, CDE-GAN incorporates dual evolution with respect to the generator(s) and discriminators into a unified evolutionary adversarial framework to conduct effective adversarial multi-objective optimization.

GAN image forensics Generative Adversarial Network +1

A Spatial-Temporal Attentive Network with Spatial Continuity for Trajectory Prediction

no code implementations13 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.

Trajectory Prediction

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