17 citations · 69 across the 16 of their papers we have counts for
16 papers
D3G: Exploring Gaussian Prior for Temporal Sentence Grounding with Glance Annotation
Hanjun Li, Xiujun Shu, Sunan He +5
Temporal sentence grounding (TSG) aims to locate a specific moment from an untrimmed video with a given natural language query. Recently, weakly supervised methods still have a lar…
Coarse-to-Fine: Learning Compact Discriminative Representation for Single-Stage Image Retrieval
Yunquan Zhu, Xinkai Gao, Bo Ke +2
Image retrieval targets to find images from a database that are visually similar to the query image. Two-stage methods following retrieve-and-rerank paradigm have achieved excellen…
Unified and Dynamic Graph for Temporal Character Grouping in Long Videos
Xiujun Shu, Wei Wen, Liangsheng Xu +6
Video temporal character grouping locates appearing moments of major characters within a video according to their identities. To this end, recent works have evolved from unsupervis…
Collaborative Noisy Label Cleaner: Learning Scene-aware Trailers for Multi-modal Highlight Detection in Movies
Bei Gan, Xiujun Shu, Ruizhi Qiao +4
Movie highlights stand out of the screenplay for efficient browsing and play a crucial role on social media platforms. Based on existing efforts, this work has two observations: (1…
See Finer, See More: Implicit Modality Alignment for Text-based Person Retrieval
Xiujun Shu, Wei Wen, Haoqian Wu +5
Text-based person retrieval aims to find the query person based on a textual description. The key is to learn a common latent space mapping between visual-textual modalities. To ac…
VLMAE: Vision-Language Masked Autoencoder
Sunan He, Taian Guo, Tao Dai +4
Image and language modeling is of crucial importance for vision-language pre-training (VLP), which aims to learn multi-modal representations from large-scale paired image-text data…
Exploiting Feature Diversity for Make-up Temporal Video Grounding
Xiujun Shu, Wei Wen, Taian Guo +3
This technical report presents the 3rd winning solution for MTVG, a new task introduced in the 4-th Person in Context (PIC) Challenge at ACM MM 2022. MTVG aims at localizing the te…
Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge Transfer
Sunan He, Taian Guo, Tao Dai +3
Real-world recognition system often encounters the challenge of unseen labels. To identify such unseen labels, multi-label zero-shot learning (ML-ZSL) focuses on transferring knowl…
Scene Consistency Representation Learning for Video Scene Segmentation
Haoqian Wu, Keyu Chen, Yanan Luo +5
A long-term video, such as a movie or TV show, is composed of various scenes, each of which represents a series of shots sharing the same semantic story. Spotting the correct scene…
Head and Body: Unified Detector and Graph Network for Person Search in Media
Xiujun Shu, Yusheng Tao, Ruizhi Qiao +3
Person search in media has seen increasing potential in Internet applications, such as video clipping and character collection. This task is common but overlooked by previous perso…
Novelty Detection via Contrastive Learning with Negative Data Augmentation
Chengwei Chen, Yuan Xie, Shaohui Lin +5
Novelty detection is the process of determining whether a query example differs from the learned training distribution. Previous methods attempt to learn the representation of the…
Contrastive Learning for Compact Single Image Dehazing
Haiyan Wu, Yanyun Qu, Shaohui Lin +5
Single image dehazing is a challenging ill-posed problem due to the severe information degeneration. However, existing deep learning based dehazing methods only adopt clear images…
Visually Aligned Word Embeddings for Improving Zero-shot Learning
Ruizhi Qiao, Lingqiao Liu, Chunhua Shen +1
Zero-shot learning (ZSL) highly depends on a good semantic embedding to connect the seen and unseen classes. Recently, distributed word embeddings (DWE) pre-trained from large text…
Structured Learning of Tree Potentials in CRF for Image Segmentation
Fayao Liu, Guosheng Lin, Ruizhi Qiao +1
We propose a new approach to image segmentation, which exploits the advantages of both conditional random fields (CRFs) and decision trees. In the literature, the potential functio…
Less is more: zero-shot learning from online textual documents with noise suppression
Ruizhi Qiao, Lingqiao Liu, Chunhua Shen +1
Classifying a visual concept merely from its associated online textual source, such as a Wikipedia article, is an attractive research topic in zero-shot learning because it allevia…
Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition
Ruizhi Qiao, Lingqiao Liu, Chunhua Shen +1
The introduction of low-cost RGB-D sensors has promoted the research in skeleton-based human action recognition. Devising a representation suitable for characterising actions on th…