25 citations · 73 across the 18 of their papers we have counts for
18 papers
WRF4CIR: Weight-Regularized Fine-Tuning Network for Composed Image Retrieval
Yizhuo Xu, Chaojian Yu, Yuanjie Shao +3
Composed Image Retrieval (CIR) task aims to retrieve target images based on reference images and modification texts. Current CIR methods primarily rely on fine-tuning vision-langua…
Adjustable Text-Guided Backdoor Attacks with Natural-Word Triggers on Multimodal Pretrained Models
Yiyang Zhang, Chaojian Yu, Ziming Hong +4
This paper presents Text-Guided Backdoor (TGB), an adjustable backdoor attack against multimodal pretrained models that uses natural-word triggers, namely words that can naturally…
Learning Unpaired Image Dehazing with Physics-based Rehazy Generation
Haoyou Deng, Zhiqiang Li, Feng Zhang +6
Overfitting to synthetic training pairs remains a critical challenge in image dehazing, leading to poor generalization capability to real-world scenarios. To address this issue, ex…
NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results
Yuqian Fu, Xingyu Qiu, Bin Ren +59
Cross-Domain Few-Shot Object Detection (CD-FSOD) poses significant challenges to existing object detection and few-shot detection models when applied across domains. In conjunction…
Object-Aware Video Matting with Cross-Frame Guidance
Huayu Zhang, Dongyue Wu, Yuanjie Shao +2
Recently, trimap-free methods have drawn increasing attention in human video matting due to their promising performance. Nevertheless, these methods still suffer from the lack of d…
CTR-Driven Advertising Image Generation with Multimodal Large Language Models
Xingye Chen, Wei Feng, Zhenbang Du +16
In web data, advertising images are crucial for capturing user attention and improving advertising effectiveness. Most existing methods generate background for products primarily f…
Open-Vocabulary Semantic Segmentation with Image Embedding Balancing
Xiangheng Shan, Dongyue Wu, Guilin Zhu +3
Open-vocabulary semantic segmentation is a challenging task, which requires the model to output semantic masks of an image beyond a close-set vocabulary. Although many efforts have…
Few-Shot Object Detection: Research Advances and Challenges
Zhimeng Xin, Shiming Chen, Tianxu Wu +3
Object detection as a subfield within computer vision has achieved remarkable progress, which aims to accurately identify and locate a specific object from images or videos. Such m…
Adaptive Semantic Consistency for Cross-domain Few-shot Classification
Hengchu Lu, Yuanjie Shao, Xiang Wang +1
Cross-domain few-shot classification (CD-FSC) aims to identify novel target classes with a few samples, assuming that there exists a domain shift between source and target domains.…
Context-aware Proposal Network for Temporal Action Detection
Xiang Wang, Huaxin Zhang, Shiwei Zhang +3
This technical report presents our first place winning solution for temporal action detection task in CVPR-2022 AcitivityNet Challenge. The task aims to localize temporal boundarie…
Multi-Centroid Representation Network for Domain Adaptive Person Re-ID
Yuhang Wu, Tengteng Huang, Haotian Yao +5
Recently, many approaches tackle the Unsupervised Domain Adaptive person re-identification (UDA re-ID) problem through pseudo-label-based contrastive learning. During training, a u…
Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior
Feng Zhang, Yuanjie Shao, Yishi Sun +3
Deep learning-based methods for low-light image enhancement typically require enormous paired training data, which are impractical to capture in real-world scenarios. Recently, uns…
CondNet: Conditional Classifier for Scene Segmentation
Changqian Yu, Yuanjie Shao, Changxin Gao +1
The fully convolutional network (FCN) has achieved tremendous success in dense visual recognition tasks, such as scene segmentation. The last layer of FCN is typically a global cla…
OadTR: Online Action Detection with Transformers
Xiang Wang, Shiwei Zhang, Zhiwu Qing +4
Most recent approaches for online action detection tend to apply Recurrent Neural Network (RNN) to capture long-range temporal structure. However, RNN suffers from non-parallelism…
Weakly-Supervised Temporal Action Localization Through Local-Global Background Modeling
Xiang Wang, Zhiwu Qing, Ziyuan Huang +6
Weakly-Supervised Temporal Action Localization (WS-TAL) task aims to recognize and localize temporal starts and ends of action instances in an untrimmed video with only video-level…
Self-Supervised Learning for Semi-Supervised Temporal Action Proposal
Xiang Wang, Shiwei Zhang, Zhiwu Qing +3
Self-supervised learning presents a remarkable performance to utilize unlabeled data for various video tasks. In this paper, we focus on applying the power of self-supervised metho…
Domain Adaptation for Image Dehazing
Yuanjie Shao, Lerenhan Li, Wenqi Ren +2
Image dehazing using learning-based methods has achieved state-of-the-art performance in recent years. However, most existing methods train a dehazing model on synthetic hazy image…
GTNet: Generative Transfer Network for Zero-Shot Object Detection
Shizhen Zhao, Changxin Gao, Yuanjie Shao +4
We propose a Generative Transfer Network (GTNet) for zero shot object detection (ZSD). GTNet consists of an Object Detection Module and a Knowledge Transfer Module. The Object Dete…