43 citations · 84 across the 9 of their papers we have counts for
8 papers · 1 filter
Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding
Qingxing Cao, Bailin Li, Xiaodan Liang +2
Though beneficial for encouraging the Visual Question Answering (VQA) models to discover the underlying knowledge by exploiting the input-output correlation beyond image and text c…
Linguistically Driven Graph Capsule Network for Visual Question Reasoning
Qingxing Cao, Xiaodan Liang, Keze Wang +1
Recently, studies of visual question answering have explored various architectures of end-to-end networks and achieved promising results on both natural and synthetic datasets, whi…
Explainable High-order Visual Question Reasoning: A New Benchmark and Knowledge-routed Network
Qingxing Cao, Bailin Li, Xiaodan Liang +1
Explanation and high-order reasoning capabilities are crucial for real-world visual question answering with diverse levels of inference complexity (e.g., what is the dog that is ne…
Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning
Yukai Shi, Guanbin Li, Qingxing Cao +2
Face hallucination is a domain-specific super-resolution problem that aims to generate a high-resolution (HR) face image from a low-resolution~(LR) input. In contrast to the existi…
Interpretable Visual Question Answering by Reasoning on Dependency Trees
Qingxing Cao, Bailin Li, Xiaodan Liang +1
Collaborative reasoning for understanding image-question pairs is a very critical but underexplored topic in interpretable visual question answering systems. Although very recent s…
Visual Question Reasoning on General Dependency Tree
Qingxing Cao, Xiaodan Liang, Bailing Li +2
The collaborative reasoning for understanding each image-question pair is very critical but under-explored for an interpretable Visual Question Answering (VQA) system. Although ver…
Attention-Aware Face Hallucination via Deep Reinforcement Learning
Qingxing Cao, Liang Lin, Yukai Shi +2
Face hallucination is a domain-specific super-resolution problem with the goal to generate high-resolution (HR) faces from low-resolution (LR) input images. In contrast to existing…
Recognizing Focal Liver Lesions in Contrast-Enhanced Ultrasound with Discriminatively Trained Spatio-Temporal Model
Xiaodan Liang, Qingxing Cao, Rui Huang +1
The aim of this study is to provide an automatic computational framework to assist clinicians in diagnosing Focal Liver Lesions (FLLs) in Contrast-Enhancement Ultrasound (CEUS). We…