activity
20182022
most citedOn Distinctive Image Captioning via Comparing and Reweighting

32 citations · 52 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV202232 cited

On Distinctive Image Captioning via Comparing and Reweighting

Jiuniu Wang, Wenjia Xu, Qingzhong Wang +1

Recent image captioning models are achieving impressive results based on popular metrics, i.e., BLEU, CIDEr, and SPICE. However, focusing on the most popular metrics that only cons…

cs.CV20202 cited

Compare and Reweight: Distinctive Image Captioning Using Similar Images Sets

Jiuniu Wang, Wenjia Xu, Qingzhong Wang +1

A wide range of image captioning models has been developed, achieving significant improvement based on popular metrics, such as BLEU, CIDEr, and SPICE. However, although the genera…

cs.CV2019

Towards Diverse and Accurate Image Captions via Reinforcing Determinantal Point Process

Qingzhong Wang, Antoni B. Chan

Although significant progress has been made in the field of automatic image captioning, it is still a challenging task. Previous works normally pay much attention to improving the…

cs.CV201918 cited

Describing like humans: on diversity in image captioning

Qingzhong Wang, Antoni B. Chan

Recently, the state-of-the-art models for image captioning have overtaken human performance based on the most popular metrics, such as BLEU, METEOR, ROUGE, and CIDEr. Does this mea…

cs.CV2018

Gated Hierarchical Attention for Image Captioning

Qingzhong Wang, Antoni B. Chan

Attention modules connecting encoder and decoders have been widely applied in the field of object recognition, image captioning, visual question answering and neural machine transl…

cs.CV2018

CNN+CNN: Convolutional Decoders for Image Captioning

Qingzhong Wang, Antoni B. Chan

Image captioning is a challenging task that combines the field of computer vision and natural language processing. A variety of approaches have been proposed to achieve the goal of…