Search Results for author: Guangyi Chen

Found 32 papers, 21 papers with code

Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification

no code implementations ECCV 2020 Guangyi Chen, Yuhao Lu, Jiwen Lu, Jie Zhou

Experimental results demonstrate that our DCML method explores credible and valuable training data and improves the performance of unsupervised domain adaptation.

Metric Learning Person Re-Identification +2

Temporal Coherence or Temporal Motion: Which is More Critical for Video-based Person Re-identification?

no code implementations ECCV 2020 Guangyi Chen, Yongming Rao, Jiwen Lu, Jie zhou

Specifically, we disentangle the video representation into the temporal coherence and motion parts and randomly change the scale of the temporal motion features as the adversarial noise.

Video-Based Person Re-Identification

Federated Causal Discovery from Heterogeneous Data

1 code implementation20 Feb 2024 Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang

This discrepancy has motivated the development of federated causal discovery (FCD) approaches.

Causal Discovery

Learning Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition

no code implementations20 Feb 2024 Yuke Li, Guangyi Chen, Ben Abramowitz, Stefano Anzellott, Donglai Wei

Moreover, we validate that the learned temporal dynamic transition and temporal dynamic generation modules possess transferable qualities.

Few-Shot action recognition Few Shot Action Recognition +1

Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models

1 code implementation19 Feb 2024 Loka Li, Guangyi Chen, Yusheng Su, Zhenhao Chen, Yixuan Zhang, Eric Xing, Kun Zhang

We have experimentally observed that LLMs possess the capability to understand the "confidence" in their own responses.

CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process

no code implementations25 Jan 2024 Guangyi Chen, Yifan Shen, Zhenhao Chen, Xiangchen Song, Yuewen Sun, Weiran Yao, Xiao Liu, Kun Zhang

Identifying the underlying time-delayed latent causal processes in sequential data is vital for grasping temporal dynamics and making downstream reasoning.

Learning Socio-Temporal Graphs for Multi-Agent Trajectory Prediction

no code implementations22 Dec 2023 Yuke Li, Lixiong Chen, Guangyi Chen, Ching-Yao Chan, Kun Zhang, Stefano Anzellotti, Donglai Wei

In order to predict a pedestrian's trajectory in a crowd accurately, one has to take into account her/his underlying socio-temporal interactions with other pedestrians consistently.

Trajectory Prediction

Identifying Semantic Component for Robust Molecular Property Prediction

1 code implementation8 Nov 2023 Zijian Li, Zunhong Xu, Ruichu Cai, Zhenhui Yang, Yuguang Yan, Zhifeng Hao, Guangyi Chen, Kun Zhang

Specifically, we first formulate the data generation process from the atom level to the molecular level, where the latent space is split into SI substructures, SR substructures, and SR atom variables.

Molecular Property Prediction Property Prediction

Temporally Disentangled Representation Learning under Unknown Nonstationarity

1 code implementation NeurIPS 2023 Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric Xing, Kun Zhang

In unsupervised causal representation learning for sequential data with time-delayed latent causal influences, strong identifiability results for the disentanglement of causally-related latent variables have been established in stationary settings by leveraging temporal structure.

Disentanglement

Subspace Identification for Multi-Source Domain Adaptation

1 code implementation NeurIPS 2023 Zijian Li, Ruichu Cai, Guangyi Chen, Boyang Sun, Zhifeng Hao, Kun Zhang

To mitigate the need for these strict assumptions, we propose a subspace identification theory that guarantees the disentanglement of domain-invariant and domain-specific variables under less restrictive constraints regarding domain numbers and transformation properties, thereby facilitating domain adaptation by minimizing the impact of domain shifts on invariant variables.

Disentanglement Domain Adaptation +1

Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment

1 code implementation24 Aug 2023 Sheng Zhang, Muzammal Naseer, Guangyi Chen, Zhiqiang Shen, Salman Khan, Kun Zhang, Fahad Khan

To address this challenge, we propose the Self Structural Semantic Alignment (S^3A) framework, which extracts the structural semantic information from unlabeled data while simultaneously self-learning.

Self-Learning Zero-Shot Learning

Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer

1 code implementation ICCV 2023 Guangyi Chen, Xiao Liu, Guangrun Wang, Kun Zhang, Philip H. S. Torr, Xiao-Ping Zhang, Yansong Tang

To bridge these gaps, in this paper, we propose Tem-Adapter, which enables the learning of temporal dynamics and complex semantics by a visual Temporal Aligner and a textual Semantic Aligner.

Question Answering Video Question Answering

Language-free Compositional Action Generation via Decoupling Refinement

1 code implementation7 Jul 2023 Xiao Liu, Guangyi Chen, Yansong Tang, Guangrun Wang, Xiao-Ping Zhang, Ser-Nam Lim

Composing simple elements into complex concepts is crucial yet challenging, especially for 3D action generation.

Action Generation

Partial Identifiability for Domain Adaptation

no code implementations10 Jun 2023 Lingjing Kong, Shaoan Xie, Weiran Yao, Yujia Zheng, Guangyi Chen, Petar Stojanov, Victor Akinwande, Kun Zhang

In general, without further assumptions, the joint distribution of the features and the label is not identifiable in the target domain.

Unsupervised Domain Adaptation

Feature Expansion for Graph Neural Networks

1 code implementation10 May 2023 Jiaqi Sun, Lin Zhang, Guangyi Chen, Kun Zhang, Peng Xu, Yujiu Yang

Graph neural networks aim to learn representations for graph-structured data and show impressive performance, particularly in node classification.

Node Classification Representation Learning

Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction

1 code implementation CVPR 2023 Guangyi Chen, Zhenhao Chen, Shunxing Fan, Kun Zhang

Specifically, we model the trajectory sampling as a Gaussian process and construct an acquisition function to measure the potential sampling value.

Bayesian Optimization Trajectory Prediction

Adversarial Alignment for Source Free Object Detection

no code implementations11 Jan 2023 Qiaosong Chu, Shuyan Li, Guangyi Chen, Kai Li, Xiu Li

Source-free object detection (SFOD) aims to transfer a detector pre-trained on a label-rich source domain to an unlabeled target domain without seeing source data.

Object object-detection +1

PromptCAL: Contrastive Affinity Learning via Auxiliary Prompts for Generalized Novel Category Discovery

1 code implementation CVPR 2023 Sheng Zhang, Salman Khan, Zhiqiang Shen, Muzammal Naseer, Guangyi Chen, Fahad Khan

The GNCD setting aims to categorize unlabeled training data coming from known and novel classes by leveraging the information of partially labeled known classes.

Graph Generation

Temporally Disentangled Representation Learning

no code implementations24 Oct 2022 Weiran Yao, Guangyi Chen, Kun Zhang

In this work, we establish the identifiability theories of nonparametric latent causal processes from their nonlinear mixtures under fixed temporal causal influences and analyze how distribution changes can further benefit the disentanglement.

Disentanglement

PLOT: Prompt Learning with Optimal Transport for Vision-Language Models

1 code implementation3 Oct 2022 Guangyi Chen, Weiran Yao, Xiangchen Song, Xinyue Li, Yongming Rao, Kun Zhang

To solve this problem, we propose to apply optimal transport to match the vision and text modalities.

FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment

1 code implementation CVPR 2022 Jinglin Xu, Yongming Rao, Xumin Yu, Guangyi Chen, Jie zhou, Jiwen Lu

Most existing action quality assessment methods rely on the deep features of an entire video to predict the score, which is less reliable due to the non-transparent inference process and poor interpretability.

Action Quality Assessment

Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion

2 code implementations CVPR 2022 Tianpei Gu, Guangyi Chen, Junlong Li, Chunze Lin, Yongming Rao, Jie zhou, Jiwen Lu

Human behavior has the nature of indeterminacy, which requires the pedestrian trajectory prediction system to model the multi-modality of future motion states.

Pedestrian Trajectory Prediction Trajectory Prediction

Learning Latent Causal Dynamics

no code implementations10 Feb 2022 Weiran Yao, Guangyi Chen, Kun Zhang

Specifically, the framework factorizes unknown distribution shifts into transition distribution changes caused by fixed dynamics and time-varying latent causal relations, and by global changes in observation.

Time Series Time Series Analysis

Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

1 code implementation ICCV 2021 Yongming Rao, Guangyi Chen, Jiwen Lu, Jie zhou

Unlike most existing methods that learn visual attention based on conventional likelihood, we propose to learn the attention with counterfactual causality, which provides a tool to measure the attention quality and a powerful supervisory signal to guide the learning process.

Causal Inference counterfactual +6

Person Re-identification via Attention Pyramid

1 code implementation11 Aug 2021 Guangyi Chen, Tianpei Gu, Jiwen Lu, Jin-An Bao, Jie zhou

Experimental results demonstrate the superiority of our method, which outperforms the state-of-the-art methods by a large margin with limited computational cost.

Person Re-Identification

Personalized Trajectory Prediction via Distribution Discrimination

1 code implementation ICCV 2021 Guangyi Chen, Junlong Li, Nuoxing Zhou, Liangliang Ren, Jiwen Lu

In this paper, we present a distribution discrimination (DisDis) method to predict personalized motion patterns by distinguishing the potential distributions.

Trajectory Prediction

Human Trajectory Prediction via Counterfactual Analysis

1 code implementation ICCV 2021 Guangyi Chen, Junlong Li, Jiwen Lu, Jie zhou

Most existing methods learn to predict future trajectories by behavior clues from history trajectories and interaction clues from environments.

Autonomous Vehicles counterfactual +1

Self-Critical Attention Learning for Person Re-Identification

no code implementations ICCV 2019 Guangyi Chen, Chunze Lin, Liangliang Ren, Jiwen Lu, Jie Zhou

Unlike most existing methods which train the attention mechanism in a weakly-supervised manner and ignore the attention confidence level, we learn the attention with a critic which measures the attention quality and provides a powerful supervisory signal to guide the learning process.

Person Re-Identification

Deep Meta Metric Learning

1 code implementation ICCV 2019 Guangyi Chen, Tianren Zhang, Jiwen Lu, Jie Zhou

In this paper, we present a deep meta metric learning (DMML) approach for visual recognition.

Face Verification Metric Learning +2

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