124 citations · 594 across the 48 of their papers we have counts for
48 papers · 1 filter
Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer Learning
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +4
Recently, large-scale pre-trained language-image models like CLIP have shown extraordinary capabilities for understanding spatial contents, but naively transferring such models to…
Towards General Low-Light Raw Noise Synthesis and Modeling
Feng Zhang, Bin Xu, Zhiqiang Li +4
Modeling and synthesizing low-light raw noise is a fundamental problem for computational photography and image processing applications. Although most recent works have adopted phys…
HR-Pro: Point-supervised Temporal Action Localization via Hierarchical Reliability Propagation
Huaxin Zhang, Xiang Wang, Xiaohao Xu +3
Point-supervised Temporal Action Localization (PSTAL) is an emerging research direction for label-efficient learning. However, current methods mainly focus on optimizing the networ…
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.…
PLIP: Language-Image Pre-training for Person Representation Learning
Jialong Zuo, Jiahao Hong, Feng Zhang +5
Language-image pre-training is an effective technique for learning powerful representations in general domains. However, when directly turning to person representation learning, th…
MoLo: Motion-augmented Long-short Contrastive Learning for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Zhiwu Qing +4
Current state-of-the-art approaches for few-shot action recognition achieve promising performance by conducting frame-level matching on learned visual features. However, they gener…
CLIP-guided Prototype Modulating for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Jun Cen +4
Learning from large-scale contrastive language-image pre-training like CLIP has shown remarkable success in a wide range of downstream tasks recently, but it is still under-explore…
Semantic Segmentation via Pixel-to-Center Similarity Calculation
Dongyue Wu, Zilin Guo, Aoyan Li +3
Since the fully convolutional network has achieved great success in semantic segmentation, lots of works have been proposed focusing on extracting discriminative pixel feature repr…
Parallel Reasoning Network for Human-Object Interaction Detection
Huan Peng, Fenggang Liu, Yangguang Li +4
Human-Object Interaction (HOI) detection aims to learn how human interacts with surrounding objects. Previous HOI detection frameworks simultaneously detect human, objects and thei…
HyRSM++: Hybrid Relation Guided Temporal Set Matching for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Zhiwu Qing +4
Recent attempts mainly focus on learning deep representations for each video individually under the episodic meta-learning regime and then performing temporal alignment to match qu…
Cross Attention Based Style Distribution for Controllable Person Image Synthesis
Xinyue Zhou, Mingyu Yin, Xinyuan Chen +3
Controllable person image synthesis task enables a wide range of applications through explicit control over body pose and appearance. In this paper, we propose a cross attention ba…
MAR: Masked Autoencoders for Efficient Action Recognition
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +5
Standard approaches for video recognition usually operate on the full input videos, which is inefficient due to the widely present spatio-temporal redundancy in videos. Recent prog…
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…
Hybrid Relation Guided Set Matching for Few-shot Action Recognition
Xiang Wang, Shiwei Zhang, Zhiwu Qing +5
Current few-shot action recognition methods reach impressive performance by learning discriminative features for each video via episodic training and designing various temporal ali…
Learning from Untrimmed Videos: Self-Supervised Video Representation Learning with Hierarchical Consistency
Zhiwu Qing, Shiwei Zhang, Ziyuan Huang +6
Natural videos provide rich visual contents for self-supervised learning. Yet most existing approaches for learning spatio-temporal representations rely on manually trimmed videos,…
Style Transformer for Image Inversion and Editing
Xueqi Hu, Qiusheng Huang, Zhengyi Shi +4
Existing GAN inversion methods fail to provide latent codes for reliable reconstruction and flexible editing simultaneously. This paper presents a transformer-based image inversion…
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…
Modality-Aware Triplet Hard Mining for Zero-shot Sketch-Based Image Retrieval
Zongheng Huang, YiFan Sun, Chuchu Han +2
This paper tackles the Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) problem from the viewpoint of cross-modality metric learning. This task has two characteristics: 1) the zero…
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…
Attribute-specific Control Units in StyleGAN for Fine-grained Image Manipulation
Rui Wang, Jian Chen, Gang Yu +4
Image manipulation with StyleGAN has been an increasing concern in recent years.Recent works have achieved tremendous success in analyzing several semantic latent spaces to edit th…
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…
Weakly Supervised Person Search with Region Siamese Networks
Chuchu Han, Kai Su, Dongdong Yu +5
Supervised learning is dominant in person search, but it requires elaborate labeling of bounding boxes and identities. Large-scale labeled training data is often difficult to colle…
ParamCrop: Parametric Cubic Cropping for Video Contrastive Learning
Zhiwu Qing, Ziyuan Huang, Shiwei Zhang +5
The central idea of contrastive learning is to discriminate between different instances and force different views from the same instance to share the same representation. To avoid…
Exploring Stronger Feature for Temporal Action Localization
Zhiwu Qing, Xiang Wang, Ziyuan Huang +6
Temporal action localization aims to localize starting and ending time with action category. Limited by GPU memory, mainstream methods pre-extract features for each video. Therefor…