activity
20202026
most citedSCGAN: Saliency Map-guided Colorization with Generative Adversarial Network

80 citations · 91 across the 5 of their papers we have counts for

collaborators

5 papers

cs.MM2026

Omni-C: Compressing Heterogeneous Modalities into a Single Dense Encoder

Kin Wai Lau, Yasar Abbas Ur Rehman, Lai-Man Po +1

Recent multimodal systems often rely on separate expert modality encoders which cause linearly scaling complexity and computational overhead with added modalities. While unified Om…

cs.LG2024

FedRepOpt: Gradient Re-parametrized Optimizers in Federated Learning

Kin Wai Lau, Yasar Abbas Ur Rehman, Pedro Porto Buarque de Gusmão +3

Federated Learning (FL) has emerged as a privacy-preserving method for training machine learning models in a distributed manner on edge devices. However, on-device models face inhe…

cs.CV2023★ 6 cited

L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning

Yasar Abbas Ur Rehman, Yan Gao, Pedro Porto Buarque de Gusmão +3

The ubiquity of camera-enabled devices has led to large amounts of unlabeled image data being produced at the edge. The integration of self-supervised learning (SSL) and federated…

cs.CV2020★ 80 cited

SCGAN: Saliency Map-guided Colorization with Generative Adversarial Network

Yuzhi Zhao, Lai-Man Po, Kwok-Wai Cheung +2

Given a grayscale photograph, the colorization system estimates a visually plausible colorful image. Conventional methods often use semantics to colorize grayscale images. However,…

eess.IV2020★ 5 cited

UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results

Yuqian Zhou, Michael Kwan, Kyle Tolentino +42

This paper is the report of the first Under-Display Camera (UDC) image restoration challenge in conjunction with the RLQ workshop at ECCV 2020. The challenge is based on a newly-co…