5 papers
FlexCast: Adaptive Weather Forecasting from Arbitrary Field Sets
Yuang Zhang, Chen Hui, Weisi Lin +4
Most deep learning weather models assign a fixed set of variables and pressure levels to predefined channels, limiting transfer across atmospheric field configurations. This depend…
Shape Distribution Matters: Shape-Specific Mixture-of-Experts for Amodal Segmentation Under Diverse Occlusions
Zhixuan Li, Yujia Liu, Chen Hui +3
Amodal segmentation aims to predict complete object masks covering both visible and occluded regions, serving as a critical foundation for robust multimedia scene understanding and…
Single Point, Full Mask: Velocity-Guided Level Set Evolution for End-to-End Amodal Segmentation
Zhixuan Li, Yujia Liu, Chen Hui +2
Amodal segmentation aims to recover complete object shapes, including occluded regions, serving as an essential technique for user-centric multimedia authoring and object-level vis…
Unveiling the Invisible: Reasoning Complex Occlusions Amodally with AURA
Zhixuan Li, Hyunse Yoon, Sanghoon Lee +1
Amodal segmentation aims to infer the complete shape of occluded objects, even when the occluded region's appearance is unavailable. However, current amodal segmentation methods la…
BEAT: Balanced Frequency Adaptive Tuning for Long-Term Time-Series Forecasting
Zhixuan Li, Naipeng Chen, Seonghwa Choi +2
Long-term time-series forecasting supports a wide range of applications, including weather prediction and electricity demand planning. Frequency-domain methods address this task by…