activity
20182021
most citedCoarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning

16 citations · 31 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2021

OpenQA: Hybrid QA System Relying on Structured Knowledge Base as well as Non-structured Data

Gaochen Wu, Bin Xu, Yuxin Qin +3

Search engines based on keyword retrieval can no longer adapt to the way of information acquisition in the era of intelligent Internet of Things due to the return of keyword relate…

cs.CV2021

Enhanced Modality Transition for Image Captioning

Ziwei Wang, Yadan Luo, Zi Huang

Image captioning model is a cross-modality knowledge discovery task, which targets at automatically describing an image with an informative and coherent sentence. To generate the c…

cs.CV2020★ 3 cited

ORD: Object Relationship Discovery for Visual Dialogue Generation

Ziwei Wang, Zi Huang, Yadan Luo +1

With the rapid advancement of image captioning and visual question answering at single-round level, the question of how to generate multi-round dialogue about visual content has no…

cs.LG2019★ 8 cited

Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling

Yadan Luo, Zi Huang, Zheng Zhang +3

Meta-learning for few-shot learning allows a machine to leverage previously acquired knowledge as a prior, thus improving the performance on novel tasks with only small amounts of…

cs.CV2019★ 4 cited

Snap and Find: Deep Discrete Cross-domain Garment Image Retrieval

Yadan Luo, Ziwei Wang, Zi Huang +2

With the increasing number of online stores, there is a pressing need for intelligent search systems to understand the item photos snapped by customers and search against large-sca…

cs.CV2018★ 16 cited

Coarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning

Yadan Luo, Ziwei Wang, Zi Huang +2

Rich high-quality annotated data is critical for semantic segmentation learning, yet acquiring dense and pixel-wise ground-truth is both labor- and time-consuming. Coarse annotatio…