Search Results for author: Guikun Chen

Found 7 papers, 3 papers with code

Neural Clustering based Visual Representation Learning

no code implementations26 Mar 2024 Guikun Chen, Xia Li, Yi Yang, Wenguan Wang

In this work, we propose feature extraction with clustering (FEC), a conceptually elegant yet surprisingly ad-hoc interpretable neural clustering framework, which views feature extraction as a process of selecting representatives from data and thus automatically captures the underlying data distribution.

Clustering Representation Learning

DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models

1 code implementation16 Jan 2024 Zongxin Yang, Guikun Chen, Xiaodi Li, Wenguan Wang, Yi Yang

Recent LLM-driven visual agents mainly focus on solving image-based tasks, which limits their ability to understand dynamic scenes, making it far from real-life applications like guiding students in laboratory experiments and identifying their mistakes.

Scheduling

A Survey on 3D Gaussian Splatting

no code implementations8 Jan 2024 Guikun Chen, Wenguan Wang

The survey concludes by identifying current challenges and suggesting potential avenues for future research in this domain.

3D Reconstruction

Compositional Zero-shot Learning via Progressive Language-based Observations

no code implementations23 Nov 2023 Lin Li, Guikun Chen, Jun Xiao, Long Chen

Compositional zero-shot learning aims to recognize unseen state-object compositions by leveraging known primitives (state and object) during training.

Compositional Zero-Shot Learning

Compositional Feature Augmentation for Unbiased Scene Graph Generation

1 code implementation ICCV 2023 Lin Li, Guikun Chen, Jun Xiao, Yi Yang, Chunping Wang, Long Chen

Specifically, we first decompose each relation triplet feature into two components: intrinsic feature and extrinsic feature, which correspond to the intrinsic characteristics and extrinsic contexts of a relation triplet, respectively.

Graph Generation Relation +1

Zero-shot Visual Relation Detection via Composite Visual Cues from Large Language Models

1 code implementation NeurIPS 2023 Lin Li, Jun Xiao, Guikun Chen, Jian Shao, Yueting Zhuang, Long Chen

To dynamically fuse different cues, we further introduce a chain-of-thought method that prompts LLMs to generate reasonable weights for different visual cues.

Relation

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