4 accepted papers
3D Scene Graph Generation (3DSGG) aims to create a structured representation of 3D environment by identifying objects as nodes and their relations as edges. Existing 3DSGG methods based on RGB-D sequences typically put much focus on the adaption of neural networks to robust node and edge feature ext…
In the realm of dialogue-to-image retrieval, the primary challenge is to fetch images from a pre-compiled database that accurately reflect the intent embedded within the dialogue history. Existing methods often overemphasize inter-modal alignment, neglecting the nuanced nature of conversational cont…
Accurately predicting inter-frame motion information plays a key role in video prediction tasks. In this paper, we propose a Motion-Aware Unit (MAU) to capture reliable inter-frame motion information by broadening the temporal receptive field of the predictive units. The MAU consists of two modules,…
Most previous learning-based methods required paired rain image data. In practice, however, paired rain data cannot be collected. Inspired by adopting unpaired data in task of translation, in this paper we present a new method for rain removal using unpaired data. We noticed that direct use of unpai…