Video Frame Interpolation (VFI) is a fascinating and challenging problem in the computer
vision (CV) field, aiming to generate non-existing frames between two consecutive video …

It is a challenging task to learn discriminative representation from images and videos, due to
large local redundancy and complex global dependency in these visual data. Convolution …

Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …

Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …

Facial Expression Recognition (FER) in the wild is extremely challenging due to occlusions,
variant head poses, face deformation and motion blur under unconstrained conditions …

Most recent approaches for online action detection tend to apply Recurrent Neural Network
(RNN) to capture long-range temporal structure. However, RNN suffers from non-parallelism …

Cross-view geo-localization is a task of matching the same geographic image from different
views, eg, unmanned aerial vehicle (UAV) and satellite. The most difficult challenges are the …

Video depth estimation aims to infer temporally consistent depth. Some methods achieve
temporal consistency by finetuning a single-image depth model during test time using …

Semantic segmentation by using remote sensing images is an efficient method for
agricultural crop classification. Recent solutions in crop segmentation are mainly deep …

Spiking camera is a bio-inspired vision sensor that mimics the sampling mechanism of the
primate fovea, which has shown great potential for capturing high-speed dynamic scenes …