17 citations · 73 across the 10 of their papers we have counts for
10 papers
LOIS: Looking Out of Instance Semantics for Visual Question Answering
Siyu Zhang, Yeming Chen, Yaoru Sun +3
Visual question answering (VQA) has been intensively studied as a multimodal task that requires effort in bridging vision and language to infer answers correctly. Recent attempts h…
Hierarchical Matching and Reasoning for Multi-Query Image Retrieval
Zhong Ji, Zhihao Li, Yan Zhang +3
As a promising field, Multi-Query Image Retrieval (MQIR) aims at searching for the semantically relevant image given multiple region-specific text queries. Existing works mainly fo…
Structural and Statistical Texture Knowledge Distillation for Semantic Segmentation
Deyi Ji, Haoran Wang, Mingyuan Tao +3
Existing knowledge distillation works for semantic segmentation mainly focus on transferring high-level contextual knowledge from teacher to student. However, low-level texture kno…
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
Lukas Hoyer, Dengxin Dai, Haoran Wang +1
In unsupervised domain adaptation (UDA), a model trained on source data (e.g. synthetic) is adapted to target data (e.g. real-world) without access to target annotation. Most previ…
Boosting Video-Text Retrieval with Explicit High-Level Semantics
Haoran Wang, Di Xu, Dongliang He +4
Video-text retrieval (VTR) is an attractive yet challenging task for multi-modal understanding, which aims to search for relevant video (text) given a query (video). Existing metho…
CODER: Coupled Diversity-Sensitive Momentum Contrastive Learning for Image-Text Retrieval
Haoran Wang, Dongliang He, Wenhao Wu +7
Image-Text Retrieval (ITR) is challenging in bridging visual and lingual modalities. Contrastive learning has been adopted by most prior arts. Except for limited amount of negative…
NSNet: Non-saliency Suppression Sampler for Efficient Video Recognition
Boyang Xia, Wenhao Wu, Haoran Wang +5
It is challenging for artificial intelligence systems to achieve accurate video recognition under the scenario of low computation costs. Adaptive inference based efficient video re…
Step-Wise Hierarchical Alignment Network for Image-Text Matching
Zhong Ji, Kexin Chen, Haoran Wang
Image-text matching plays a central role in bridging the semantic gap between vision and language. The key point to achieve precise visual-semantic alignment lies in capturing the…
Consensus-Aware Visual-Semantic Embedding for Image-Text Matching
Haoran Wang, Ying Zhang, Zhong Ji +2
Image-text matching plays a central role in bridging vision and language. Most existing approaches only rely on the image-text instance pair to learn their representations, thereby…
Saliency-Guided Attention Network for Image-Sentence Matching
Zhong Ji, Haoran Wang, Jungong Han +1
This paper studies the task of matching image and sentence, where learning appropriate representations across the multi-modal data appears to be the main challenge. Unlike previous…