Make-it-Real: Unleashing Large Multimodal Model's Ability for Painting 3D Objects with Realistic Materials

no code implementations • 25 Apr 2024 • Ye Fang, Zeyi Sun, Tong Wu, Jiaqi Wang, Ziwei Liu, Gordon Wetzstein, Dahua Lin

Physically realistic materials are pivotal in augmenting the realism of 3D assets across various applications and lighting conditions.

Gemini vs GPT-4V: A Preliminary Comparison and Combination of Vision-Language Models Through Qualitative Cases

1 code implementation • 22 Dec 2023 • Zhangyang Qi, Ye Fang, Mengchen Zhang, Zeyi Sun, Tong Wu, Ziwei Liu, Dahua Lin, Jiaqi Wang, Hengshuang Zhao

We conducted a series of structured experiments to evaluate their performance in various industrial application scenarios, offering a comprehensive perspective on their practical utility.

Alpha-CLIP: A CLIP Model Focusing on Wherever You Want

1 code implementation • 6 Dec 2023 • Zeyi Sun, Ye Fang, Tong Wu, Pan Zhang, Yuhang Zang, Shu Kong, Yuanjun Xiong, Dahua Lin, Jiaqi Wang

Alpha-CLIP not only preserves the visual recognition ability of CLIP but also enables precise control over the emphasis of image contents.

3D Generation

GPT4Point: A Unified Framework for Point-Language Understanding and Generation

1 code implementation • 5 Dec 2023 • Zhangyang Qi, Ye Fang, Zeyi Sun, Xiaoyang Wu, Tong Wu, Jiaqi Wang, Dahua Lin, Hengshuang Zhao

Multimodal Large Language Models (MLLMs) have excelled in 2D image-text comprehension and image generation, but their understanding of the 3D world is notably deficient, limiting progress in 3D language understanding and generation.

3D Generation Reading Comprehension