3 accepted papers
Fine-tuning Large Language Models (LLMs) for machine translation is effective but costly. It also increases the risk of overfitting and catastrophic forgetting, especially when training data is limited. To tackle these challenges, we propose a novel method that involves adjusting task-related layers…
We present a novel alignment-before-generation approach to tackle the challenging task of generating general 3D shapes based on 2D images or texts. Directly learning a conditional generative model from images or texts to 3D shapes is prone to producing inconsistent results with the conditions becaus…
Implicit neural 3D representation has achieved impressive results in surface or scene reconstruction and novel view synthesis, which typically uses the coordinate-based multi-layer perceptrons (MLPs) to learn a continuous scene representation. However, existing approaches, such as Neural Radiance Fi…