6 papers
G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model
Jiahui Gao, Renjie Pi, Jipeng Zhang +8
Large language models (LLMs) have shown remarkable proficiency in human-level reasoning and generation capabilities, which encourages extensive research on their application in mat…
SplatMesh: Interactive 3D Segmentation and Editing Using Mesh-Based Gaussian Splatting
Kaichen Zhou, Lanqing Hong, Xinhai Chang +7
A key challenge in fine-grained 3D-based interactive editing is the absence of an efficient representation that balances diverse modifications with high-quality view synthesis unde…
Empowering Sparse-Input Neural Radiance Fields with Dual-Level Semantic Guidance from Dense Novel Views
Yingji Zhong, Kaichen Zhou, Zhihao Li +3
Neural Radiance Fields (NeRF) have shown remarkable capabilities for photorealistic novel view synthesis. One major deficiency of NeRF is that dense inputs are typically required,…
Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data
Haonan Wang, Minbin Huang, Runhui Huang +7
Contrastive Language-Image Pre-training (CLIP) has become the standard for cross-modal image-text representation learning. Improving CLIP typically requires additional data and ret…
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models
Kaican Li, Weiyan Xie, Yongxiang Huang +5
Fine-tuning foundation models often compromises their robustness to distribution shifts. To remedy this, most robust fine-tuning methods aim to preserve the pre-trained features. H…
Implicit Concept Removal of Diffusion Models
Zhili Liu, Kai Chen, Yifan Zhang +6
Text-to-image (T2I) diffusion models often inadvertently generate unwanted concepts such as watermarks and unsafe images. These concepts, termed as the "implicit concepts", could b…