12 citations · 22 across the 5 of their papers we have counts for
6 papers
An Efficient Adaptive Compression Method for Human Perception and Machine Vision Tasks
Lei Liu, Zhenghao Chen, Zhihao Hu +1
While most existing neural image compression (NIC) and neural video compression (NVC) methodologies have achieved remarkable success, their optimization is primarily focused on hum…
Unsupervised Part Discovery via Dual Representation Alignment
Jiahao Xia, Wenjian Huang, Min Xu +4
Object parts serve as crucial intermediate representations in various downstream tasks, but part-level representation learning still has not received as much attention as other vis…
PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud Analysis
Zicheng Wang, Zhenghao Chen, Yiming Wu +3
Point cloud analysis has seen substantial advancements due to deep learning, although previous Transformer-based methods excel at modeling long-range dependencies on this task, the…
Group-aware Parameter-efficient Updating for Content-Adaptive Neural Video Compression
Zhenghao Chen, Luping Zhou, Zhihao Hu +1
Content-adaptive compression is crucial for enhancing the adaptability of the pre-trained neural codec for various contents. Although these methods have been very practical in neur…
UFDA: Universal Federated Domain Adaptation with Practical Assumptions
Xinhui Liu, Zhenghao Chen, Luping Zhou +5
Conventional Federated Domain Adaptation (FDA) approaches usually demand an abundance of assumptions, which makes them significantly less feasible for real-world situations and int…
Cross-domain Detection Transformer based on Spatial-aware and Semantic-aware Token Alignment
Jinhong Deng, Xiaoyue Zhang, Wen Li +1
Detection transformers like DETR have recently shown promising performance on many object detection tasks, but the generalization ability of those methods is still quite challengin…