45 citations · 89 across the 17 of their papers we have counts for
17 papers
Hierarchical Relation-augmented Representation Generalization for Few-shot Action Recognition
Hongyu Qu, Ling Xing, Jiachao Zhang +3
Few-shot action recognition (FSAR) aims to recognize novel action categories with few exemplars. Existing methods typically learn frame-level representations for each video by desi…
Locality-aware Cross-modal Correspondence Learning for Dense Audio-Visual Events Localization
Ling Xing, Hongyu Qu, Rui Yan +2
Dense-localization Audio-Visual Events (DAVE) aims to identify time boundaries and corresponding categories for events that are both audible and visible in a long video, where even…
AdaFPP: Adapt-Focused Bi-Propagating Prototype Learning for Panoramic Activity Recognition
Meiqi Cao, Rui Yan, Xiangbo Shu +3
Panoramic Activity Recognition (PAR) aims to identify multi-granularity behaviors performed by multiple persons in panoramic scenes, including individual activities, group activiti…
MVP-Shot: Multi-Velocity Progressive-Alignment Framework for Few-Shot Action Recognition
Hongyu Qu, Rui Yan, Xiangbo Shu +3
Recent few-shot action recognition (FSAR) methods typically perform semantic matching on learned discriminative features to achieve promising performance. However, most FSAR method…
GPT4Ego: Unleashing the Potential of Pre-trained Models for Zero-Shot Egocentric Action Recognition
Guangzhao Dai, Xiangbo Shu, Wenhao Wu +2
Vision-Language Models (VLMs), pre-trained on large-scale datasets, have shown impressive performance in various visual recognition tasks. This advancement paves the way for notabl…
Boosting Weakly-Supervised Image Segmentation via Representation, Transform, and Compensator
Chunyan Wang, Dong Zhang, Rui Yan
Weakly-supervised image segmentation (WSIS) is a critical task in computer vision that relies on image-level class labels. Multi-stage training procedures have been widely used in…
UniVTG: Towards Unified Video-Language Temporal Grounding
Kevin Qinghong Lin, Pengchuan Zhang, Joya Chen +5
Video Temporal Grounding (VTG), which aims to ground target clips from videos (such as consecutive intervals or disjoint shots) according to custom language queries (e.g., sentence…
MNet: Multi-view Encoding, Matching, and Fusion for Few-shot Fine-grained Action Recognition
Hao Tang, Jun Liu, Shuanglin Yan +3
Due to the scarcity of manually annotated data required for fine-grained video understanding, few-shot fine-grained (FS-FG) action recognition has gained significant attention, wit…
Attack-Augmentation Mixing-Contrastive Skeletal Representation Learning
Binqian Xu, Xiangbo Shu, Jiachao Zhang +2
Contrastive learning, relying on effective positive and negative sample pairs, is beneficial to learn informative skeleton representations in unsupervised skeleton-based action rec…
Egocentric Video-Language Pretraining @ Ego4D Challenge 2022
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13
In this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for four Ego4D challenge tasks, including Natural Language Query (NLQ), Moment Q…
Egocentric Video-Language Pretraining @ EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022
Kevin Qinghong Lin, Alex Jinpeng Wang, Rui Yan +9
In this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for the EPIC-KITCHENS-100 Multi-Instance Retrieval (MIR) challenge. Especially,…
Egocentric Video-Language Pretraining
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13
Video-Language Pretraining (VLP), which aims to learn transferable representation to advance a wide range of video-text downstream tasks, has recently received increasing attention…
Dual-AI: Dual-path Actor Interaction Learning for Group Activity Recognition
Mingfei Han, David Junhao Zhang, Yali Wang +4
Learning spatial-temporal relation among multiple actors is crucial for group activity recognition. Different group activities often show the diversified interactions between actor…
Video-Text Pre-training with Learned Regions
Rui Yan, Mike Zheng Shou, Yixiao Ge +4
Video-Text pre-training aims at learning transferable representations from large-scale video-text pairs via aligning the semantics between visual and textual information. State-of-…
Expansion-Squeeze-Excitation Fusion Network for Elderly Activity Recognition
Xiangbo Shu, Jiawen Yang, Rui Yan +1
This work focuses on the task of elderly activity recognition, which is a challenging task due to the existence of individual actions and human-object interactions in elderly activ…
Interactive Fusion of Multi-level Features for Compositional Activity Recognition
Rui Yan, Lingxi Xie, Xiangbo Shu +1
To understand a complex action, multiple sources of information, including appearance, positional, and semantic features, need to be integrated. However, these features are difficu…
Social Adaptive Module for Weakly-supervised Group Activity Recognition
Rui Yan, Lingxi Xie, Jinhui Tang +2
This paper presents a new task named weakly-supervised group activity recognition (GAR) which differs from conventional GAR tasks in that only video-level labels are available, yet…