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20192026
most citedLearning to Augment Expressions for Few-shot Fine-grained Facial Expression Recognition

11 citations · 11 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection

Siheng Wang, Yanshu Li, Bohan Hu +12

Open-vocabulary object detection (OVOD) enables models to recognize objects beyond predefined categories, but existing approaches remain limited in practical deployment. On the one…

cs.CV2023

GeoVLN: Learning Geometry-Enhanced Visual Representation with Slot Attention for Vision-and-Language Navigation

Jingyang Huo, Qiang Sun, Boyan Jiang +2

Most existing works solving Room-to-Room VLN problem only utilize RGB images and do not consider local context around candidate views, which lack sufficient visual cues about surro…

cs.CV202011 cited

Learning to Augment Expressions for Few-shot Fine-grained Facial Expression Recognition

Wenxuan Wang, Yanwei Fu, Qiang Sun +7

Affective computing and cognitive theory are widely used in modern human-computer interaction scenarios. Human faces, as the most prominent and easily accessible features, have att…

cs.CV2019

A Fine-Grained Facial Expression Database for End-to-End Multi-Pose Facial Expression Recognition

Wenxuan Wang, Qiang Sun, Tao Chen +5

The recent research of facial expression recognition has made a lot of progress due to the development of deep learning technologies, but some typical challenging problems such as…

cs.CV2019

Question Guided Modular Routing Networks for Visual Question Answering

Yanze Wu, Qiang Sun, Jianqi Ma +4

This paper studies the task of Visual Question Answering (VQA), which is topical in Multimedia community recently. Particularly, we explore two critical research problems existed i…