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20172023
most citedWhat Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation

21 citations · 75 across the 22 of their papers we have counts for

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10 papers · 1 filter

cs.CV2023

Create Your World: Lifelong Text-to-Image Diffusion

Gan Sun, Wenqi Liang, Jiahua Dong +3

Text-to-image generative models can produce diverse high-quality images of concepts with a text prompt, which have demonstrated excellent ability in image generation, image transla…

cs.CV2023

I3DOD: Towards Incremental 3D Object Detection via Prompting

Wenqi Liang, Gan Sun, Chenxi Liu +2

3D object detection has achieved significant performance in many fields, e.g., robotics system, autonomous driving, and augmented reality. However, most existing methods could caus…

cs.CV20233 cited

Heterogeneous Forgetting Compensation for Class-Incremental Learning

Jiahua Dong, Wenqi Liang, Yang Cong +1

Class-incremental learning (CIL) has achieved remarkable successes in learning new classes consecutively while overcoming catastrophic forgetting on old categories. However, most e…

cs.CV2023

Gradient-Semantic Compensation for Incremental Semantic Segmentation

Wei Cong, Yang Cong, Jiahua Dong +2

Incremental semantic segmentation aims to continually learn the segmentation of new coming classes without accessing the training data of previously learned classes. However, most…

cs.CV20202 cited

I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting

Jiahua Dong, Yang Cong, Gan Sun +2

3D object classification has attracted appealing attentions in academic researches and industrial applications. However, most existing methods need to access the training data of p…

cs.CV2020

Weakly-Supervised Cross-Domain Adaptation for Endoscopic Lesions Segmentation

Jiahua Dong, Yang Cong, Gan Sun +3

Weakly-supervised learning has attracted growing research attention on medical lesions segmentation due to significant saving in pixel-level annotation cost. However, 1) most exist…