48 citations · 96 across the 12 of their papers we have counts for
15 papers
Auto-regressive transformation for image alignment
Kanggeon Lee, Soochahn Lee, Kyoung Mu Lee
Existing methods for image alignment struggle in cases involving feature-sparse regions, extreme scale and field-of-view differences, and large deformations, often resulting in sub…
MonoNHR: Monocular Neural Human Renderer
Hongsuk Choi, Gyeongsik Moon, Matthieu Armando +3
Existing neural human rendering methods struggle with a single image input due to the lack of information in invisible areas and the depth ambiguity of pixels in visible areas. In…
Pay Attention to Hidden States for Video Deblurring: Ping-Pong Recurrent Neural Networks and Selective Non-Local Attention
JoonKyu Park, Seungjun Nah, Kyoung Mu Lee
Video deblurring models exploit information in the neighboring frames to remove blur caused by the motion of the camera and the objects. Recurrent Neural Networks~(RNNs) are often…
CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image
Reyhaneh Neshatavar, Mohsen Yavartanoo, Sanghyun Son +1
Recently, significant progress has been made on image denoising with strong supervision from large-scale datasets. However, obtaining well-aligned noisy-clean training image pairs…
HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network
JoonKyu Park, Yeonguk Oh, Gyeongsik Moon +2
Hands are often severely occluded by objects, which makes 3D hand mesh estimation challenging. Previous works often have disregarded information at occluded regions. However, we ar…
AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network
Wooseok Lee, Sanghyun Son, Kyoung Mu Lee
Blind-spot network (BSN) and its variants have made significant advances in self-supervised denoising. Nevertheless, they are still bound to synthetic noisy inputs due to less prac…