12 citations · 25 across the 27 of their papers we have counts for
6 papers · 1 filter
Visual Commonsense-aware Representation Network for Video Captioning
Pengpeng Zeng, Haonan Zhang, Lianli Gao +3
Generating consecutive descriptions for videos, i.e., Video Captioning, requires taking full advantage of visual representation along with the generation process. Existing video ca…
Dual-branch Hybrid Learning Network for Unbiased Scene Graph Generation
Chaofan Zheng, Lianli Gao, Xinyu Lyu +3
The current studies of Scene Graph Generation (SGG) focus on solving the long-tailed problem for generating unbiased scene graphs. However, most de-biasing methods overemphasize th…
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation
Xinyu Lyu, Lianli Gao, Pengpeng Zeng +2
The performance of current Scene Graph Generation (SGG) models is severely hampered by hard-to-distinguish predicates, e.g., woman-on/standing on/walking on-beach. As general SGG m…
From Pixels to Objects: Cubic Visual Attention for Visual Question Answering
Jingkuan Song, Pengpeng Zeng, Lianli Gao +1
Recently, attention-based Visual Question Answering (VQA) has achieved great success by utilizing question to selectively target different visual areas that are related to the answ…
Structured Two-stream Attention Network for Video Question Answering
Lianli Gao, Pengpeng Zeng, Jingkuan Song +4
To date, visual question answering (VQA) (i.e., image QA and video QA) is still a holy grail in vision and language understanding, especially for video QA. Compared with image QA t…
Support-set based Multi-modal Representation Enhancement for Video Captioning
Xiaoya Chen, Jingkuan Song, Pengpeng Zeng +2
Video captioning is a challenging task that necessitates a thorough comprehension of visual scenes. Existing methods follow a typical one-to-one mapping, which concentrates on a li…