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cs.CV2024
SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding
Hao Li, Changyao Tian, Jie Shao +8
The remarkable success of Large Language Models (LLMs) has extended to the multimodal domain, achieving outstanding performance in image understanding and generation. Recent effort…
cs.CV2024
PUMA: Empowering Unified MLLM with Multi-granular Visual Generation
Rongyao Fang, Chengqi Duan, Kun Wang +7
Recent advancements in multimodal foundation models have yielded significant progress in vision-language understanding. Initial attempts have also explored the potential of multimo…
cs.CV2024
Parameter-Inverted Image Pyramid Networks
Xizhou Zhu, Xue Yang, Zhaokai Wang +6
Image pyramids are commonly used in modern computer vision tasks to obtain multi-scale features for precise understanding of images. However, image pyramids process multiple resolu…