26 citations · 83 across the 30 of their papers we have counts for
14 papers · 1 filter
HybridFlow: Infusing Continuity into Masked Codebook for Extreme Low-Bitrate Image Compression
Lei Lu, Yanyue Xie, Wei Jiang +3
This paper investigates the challenging problem of learned image compression (LIC) with extreme low bitrates. Previous LIC methods based on transmitting quantized continuous featur…
Hierarchical Attention Models for Multi-Relational Graphs
Roshni G. Iyer, Wei Wang, Yizhou Sun
We present Bi-Level Attention-Based Relational Graph Convolutional Networks (BR-GCN), unique neural network architectures that utilize masked self-attentional layers with relationa…
QAQ: Quality Adaptive Quantization for LLM KV Cache
Shichen Dong, Wen Cheng, Jiayu Qin +1
The emergence of LLMs has ignited a fresh surge of breakthroughs in NLP applications, particularly in domains such as question-answering systems and text generation. As the need fo…
Think before You Leap: Content-Aware Low-Cost Edge-Assisted Video Semantic Segmentation
Mingxuan Yan, Yi Wang, Xuedou Xiao +3
Offloading computing to edge servers is a promising solution to support growing video understanding applications at resource-constrained IoT devices. Recent efforts have been made…
How Powerful Potential of Attention on Image Restoration?
Cong Wang, Jinshan Pan, Yeying Jin +5
Transformers have demonstrated their effectiveness in image restoration tasks. Existing Transformer architectures typically comprise two essential components: multi-head self-atten…
TextBlockV2: Towards Precise-Detection-Free Scene Text Spotting with Pre-trained Language Model
Jiahao Lyu, Jin Wei, Gangyan Zeng +4
Existing scene text spotters are designed to locate and transcribe texts from images. However, it is challenging for a spotter to achieve precise detection and recognition of scene…