5 citations · 21 across the 16 of their papers we have counts for
6 papers · 1 filter
Simple Supervision Is Hard to Beat: A Bitter Lesson from Sparse Target Labels in Domain-Adaptive Object Detection
Lijun Zhang, Ruinian Xu, Mudit Agrawal
Source-free domain adaptive object detection adapts a source-trained detector to an unlabeled target domain, typically through teacher-student self-training with pseudo-labels. We…
RPiAE: A Representation-Pivoted Autoencoder Enhancing Both Image Generation and Editing
Yue Gong, Hongyu Li, Shanyuan Liu +8
Diffusion models have become the dominant paradigm for image generation and editing, with latent diffusion models shifting denoising to a compact latent space for efficiency and sc…
Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models
Xiao Liu, Lijun Zhang, Deepak Ganesan +1
Vision Language Models (VLMs) are central to Visual Question Answering (VQA) systems and are typically deployed in the cloud due to their high computational demands. However, this…
Attack-Resilient Image Watermarking Using Stable Diffusion
Lijun Zhang, Xiao Liu, Antoni Viros Martin +3
Watermarking images is critical for tracking image provenance and proving ownership. With the advent of generative models, such as stable diffusion, that can create fake but realis…
Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression
Yuezhou Sun, Wenlong Zhao, Lijun Zhang +3
This paper investigates deep neural network (DNN) compression from the perspective of compactly representing and storing trained parameters. We explore the previously overlooked op…
SID-NISM: A Self-supervised Low-light Image Enhancement Framework
Lijun Zhang, Xiao Liu, Erik Learned-Miller +1
When capturing images in low-light conditions, the images often suffer from low visibility, which not only degrades the visual aesthetics of images, but also significantly degenera…