Search Results for author: Bo Wan

Found 10 papers, 8 papers with code

Exploiting CLIP for Zero-shot HOI Detection Requires Knowledge Distillation at Multiple Levels

1 code implementation10 Sep 2023 Bo Wan, Tinne Tuytelaars

In this paper, we investigate the task of zero-shot human-object interaction (HOI) detection, a novel paradigm for identifying HOIs without the need for task-specific annotations.

Human-Object Interaction Detection Knowledge Distillation +1

UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory

1 code implementation28 Aug 2023 Haiwen Diao, Bo Wan, Ying Zhang, Xu Jia, Huchuan Lu, Long Chen

Fine-tuning pre-trained models has emerged as a powerful technique in numerous domains, owing to its ability to leverage enormous pre-existing knowledge and achieve remarkable performance on downstream tasks.

Question Answering Retrieval +5

Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning

no code implementations2 Mar 2023 Bo Wan, Yongfei Liu, Desen Zhou, Tinne Tuytelaars, Xuming He

Human object interaction (HOI) detection plays a crucial role in human-centric scene understanding and serves as a fundamental building-block for many vision tasks.

Human-Object Interaction Detection Knowledge Distillation +3

Single Image 3D Object Estimation with Primitive Graph Networks

1 code implementation9 Sep 2021 Qian He, Desen Zhou, Bo Wan, Xuming He

To address those challenges, we adopt a primitive-based representation for 3D object, and propose a two-stage graph network for primitive-based 3D object estimation, which consists of a sequential proposal module and a graph reasoning module.

Object Scene Understanding

Relation-aware Instance Refinement for Weakly Supervised Visual Grounding

1 code implementation CVPR 2021 Yongfei Liu, Bo Wan, Lin Ma, Xuming He

Visual grounding, which aims to build a correspondence between visual objects and their language entities, plays a key role in cross-modal scene understanding.

Object Relation +3

Learning Cross-modal Context Graph for Visual Grounding

2 code implementations20 Nov 2019 Yongfei Liu, Bo Wan, Xiaodan Zhu, Xuming He

To address their limitations, this paper proposes a language-guided graph representation to capture the global context of grounding entities and their relations, and develop a cross-modal graph matching strategy for the multiple-phrase visual grounding task.

Graph Matching Visual Grounding

Pose-aware Multi-level Feature Network for Human Object Interaction Detection

1 code implementation ICCV 2019 Bo Wan, Desen Zhou, Yongfei Liu, Rongjie Li, Xuming He

Reasoning human object interactions is a core problem in human-centric scene understanding and detecting such relations poses a unique challenge to vision systems due to large variations in human-object configurations, multiple co-occurring relation instances and subtle visual difference between relation categories.

Human-Object Interaction Detection Object +2

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