Search Results for author: Hongbin Lin

Found 7 papers, 2 papers with code

Heterogeneous-Graph Reasoning and Fine-Grained Aggregation for Fact Checking

no code implementations FEVER (ACL) 2022 Hongbin Lin, Xianghua Fu

Fact checking is a challenging task that requires corresponding evidences to verify the property of a claim based on reasoning.

Fact Checking Graph Attention

Fully Test-Time Adaptation for Monocular 3D Object Detection

no code implementations30 May 2024 Hongbin Lin, Yifan Zhang, Shuaicheng Niu, Shuguang Cui, Zhen Li

However, applying this paradigm in Mono 3Det poses significant challenges due to OOD test data causing a remarkable decline in object detection scores.

Monocular 3D Object Detection object-detection +1

World Models for General Surgical Grasping

no code implementations28 May 2024 Hongbin Lin, Bin Li, Chun Wai Wong, Juan Rojas, Xiangyu Chu, Kwok Wai Samuel Au

Our learned visuomotor policy handles: i) unseen objects, including 5 types of target grasping objects and a robot gripper, in unstructured real-world surgery environments, and ii) disturbances in perception and control.

Pose Estimation

UNeR3D: Versatile and Scalable 3D RGB Point Cloud Generation from 2D Images in Unsupervised Reconstruction

no code implementations10 Dec 2023 Hongbin Lin, Juangui Xu, Qingfeng Xu, Zhengyu Hu, Handing Xu, Yunzhi Chen, Yongjun Hu, Zhenguo Nie

Our model significantly cuts down the training costs tied to supervised approaches and introduces RGB coloration to 3D point clouds, enriching the visual experience.

3D Reconstruction Point Cloud Generation

Imbalance-Agnostic Source-Free Domain Adaptation via Avatar Prototype Alignment

no code implementations22 May 2023 Hongbin Lin, Mingkui Tan, Yifan Zhang, Zhen Qiu, Shuaicheng Niu, Dong Liu, Qing Du, Yanxia Liu

To address this issue, we study a more practical SF-UDA task, termed imbalance-agnostic SF-UDA, where the class distributions of both the unseen source domain and unlabeled target domain are unknown and could be arbitrarily skewed.

Pseudo Label Source-Free Domain Adaptation +1

Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation

1 code implementation22 Jul 2022 Hongbin Lin, Yifan Zhang, Zhen Qiu, Shuaicheng Niu, Chuang Gan, Yanxia Liu, Mingkui Tan

2) Prototype-based alignment and replay: based on the identified label prototypes, we align both domains and enforce the model to retain previous knowledge.

Unsupervised Domain Adaptation

Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation

1 code implementation18 Jun 2021 Zhen Qiu, Yifan Zhang, Hongbin Lin, Shuaicheng Niu, Yanxia Liu, Qing Du, Mingkui Tan

(2) prototype adaptation: based on the generated source prototypes and target pseudo labels, we develop a new robust contrastive prototype adaptation strategy to align each pseudo-labeled target data to the corresponding source prototypes.

Contrastive Learning Source-Free Domain Adaptation +1

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