activity
20192023
most citedHierarchical Clustering with Hard-batch Triplet Loss for Person Re-identification

32 citations · 44 across the 12 of their papers we have counts for

collaborators

12 papers

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

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

Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation

Xinyu Shi, Dong Wei, Yu Zhang +5

Research into Few-shot Semantic Segmentation (FSS) has attracted great attention, with the goal to segment target objects in a query image given only a few annotated support images…

eess.IV2022★ 1 cited

Deformer: Towards Displacement Field Learning for Unsupervised Medical Image Registration

Jiashun Chen, Donghuan Lu, Yu Zhang +5

Recently, deep-learning-based approaches have been widely studied for deformable image registration task. However, most efforts directly map the composite image representation to s…