25 citations · 26 across the 11 of their papers we have counts for
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cs.CV2023
SYNC-CLIP: Synthetic Data Make CLIP Generalize Better in Data-Limited Scenarios
Mushui Liu, Weijie He, Ziqian Lu +1
Prompt learning is a powerful technique for transferring Vision-Language Models (VLMs) such as CLIP to downstream tasks. However, the prompt-based methods that are fine-tuned solel…
cs.CV2023
Prompt-based test-time real image dehazing: a novel pipeline
Zixuan Chen, Zewei He, Ziqian Lu +2
Existing methods attempt to improve models' generalization ability on real-world hazy images by exploring well-designed training schemes (\eg, CycleGAN, prior loss). However, most…
cs.CV2023
Accurate and lightweight dehazing via multi-receptive-field non-local network and novel contrastive regularization
Zewei He, Zixuan Chen, Jinlei Li +5
Recently, deep learning-based methods have dominated image dehazing domain. A multi-receptive-field non-local network (MRFNLN) consisting of the multi-stream feature attention bloc…