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20222024
most citedSpikformer: When Spiking Neural Network Meets Transformer

105 citations · 190 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.CV2023★ 4 cited

ChatFace: Chat-Guided Real Face Editing via Diffusion Latent Space Manipulation

Dongxu Yue, Qin Guo, Munan Ning +3

Editing real facial images is a crucial task in computer vision with significant demand in various real-world applications. While GAN-based methods have showed potential in manipul…

cs.CV2023★ 1 cited

Album Storytelling with Iterative Story-aware Captioning and Large Language Models

Munan Ning, Yujia Xie, Dongdong Chen +5

This work studies how to transform an album to vivid and coherent stories, a task we refer to as "album storytelling". While this task can help preserve memories and facilitate exp…

cs.CV2023

Temporal Contrastive Learning for Spiking Neural Networks

Haonan Qiu, Zeyin Song, Yanqi Chen +6

Biologically inspired spiking neural networks (SNNs) have garnered considerable attention due to their low-energy consumption and spatio-temporal information processing capabilitie…

cs.CV2023★ 6 cited

Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental Learning

Zeyin Song, Yifan Zhao, Yujun Shi +3

Few-shot class-incremental learning (FSCIL) aims at learning to classify new classes continually from limited samples without forgetting the old classes. The mainstream framework t…

cs.CV2023

MADAv2: Advanced Multi-Anchor Based Active Domain Adaptation Segmentation

Munan Ning, Donghuan Lu, Yujia Xie +6

Unsupervised domain adaption has been widely adopted in tasks with scarce annotated data. Unfortunately, mapping the target-domain distribution to the source-domain unconditionally…

cs.CV2022★ 3 cited

Improving Vision Transformers by Revisiting High-frequency Components

Jiawang Bai, Li Yuan, Shu-Tao Xia +3

The transformer models have shown promising effectiveness in dealing with various vision tasks. However, compared with training Convolutional Neural Network (CNN) models, training…