25 citations · 42 across the 8 of their papers we have counts for
5 papers · 1 filter
Relational Graph Learning for Grounded Video Description Generation
Wenqiao Zhang, Xin Eric Wang, Siliang Tang +5
Grounded video description (GVD) encourages captioning models to attend to appropriate video regions (e.g., objects) dynamically and generate a description. Such a setting can help…
MAGIC: Multimodal relAtional Graph adversarIal inferenCe for Diverse and Unpaired Text-based Image Captioning
Wenqiao Zhang, Haochen Shi, Jiannan Guo +5
Text-based image captioning (TextCap) requires simultaneous comprehension of visual content and reading the text of images to generate a natural language description. Although a ta…
Consensus Graph Representation Learning for Better Grounded Image Captioning
Wenqiao Zhang, Haochen Shi, Siliang Tang +3
The contemporary visual captioning models frequently hallucinate objects that are not actually in a scene, due to the visual misclassification or over-reliance on priors that resul…
Adaptive Hierarchical Graph Reasoning with Semantic Coherence for Video-and-Language Inference
Juncheng Li, Siliang Tang, Linchao Zhu +5
Video-and-Language Inference is a recently proposed task for joint video-and-language understanding. This new task requires a model to draw inference on whether a natural language…
Empower Distantly Supervised Relation Extraction with Collaborative Adversarial Training
Tao Chen, Haochen Shi, Liyuan Liu +4
With recent advances in distantly supervised (DS) relation extraction (RE), considerable attention is attracted to leverage multi-instance learning (MIL) to distill high-quality su…