activity
20242026
collaborators

6 papers

cs.CV2026

Head-Aware Key-Value Compression for Efficient Autoregressive Image Generation

Guotao Liang, Baoquan Zhang, Zhiyuan Wen +1

Autoregressive (AR) visual generation has achieved remarkable performance but suffers from high memory usage and low throughput, as it requires caching previously generated visual…

cs.CV2026

SJD-PV: Speculative Jacobi Decoding with Phrase Verification for Autoregressive Image Generation

Zhehao Yu, Baoquan Zhang, Bingqi Shan +5

Autoregressive (AR) image models have recently demonstrated remarkable generative capability, but their sequential nature results in significant inference latency. Existing trainin…

cs.CV2025

Improved Masked Image Generation with Knowledge-Augmented Token Representations

Guotao Liang, Baoquan Zhang, Zhiyuan Wen +2

Masked image generation (MIG) has demonstrated remarkable efficiency and high-fidelity images by enabling parallel token prediction. Existing methods typically rely solely on the m…

cs.CV2025

Towards Improved Text-Aligned Codebook Learning: Multi-Hierarchical Codebook-Text Alignment with Long Text

Guotao Liang, Baoquan Zhang, Zhiyuan Wen +4

Image quantization is a crucial technique in image generation, aimed at learning a codebook that encodes an image into a discrete token sequence. Recent advancements have seen rese…

cs.CV2024

AsyncDSB: Schedule-Asynchronous Diffusion Schrödinger Bridge for Image Inpainting

Zihao Han, Baoquan Zhang, Lisai Zhang +6

Image inpainting is an important image generation task, which aims to restore corrupted image from partial visible area. Recently, diffusion Schrödinger bridge methods effectively…

cs.CV2024

LG-VQ: Language-Guided Codebook Learning

Guotao Liang, Baoquan Zhang, Yaowei Wang +6

Vector quantization (VQ) is a key technique in high-resolution and high-fidelity image synthesis, which aims to learn a codebook to encode an image with a sequence of discrete code…