3 accepted papers
Controllable generation through Stable Diffusion (SD) fine-tuning aims to improve fidelity, safety, and alignment with human guidance. Existing reinforcement learning from human feedback methods usually rely on predefined heuristic reward functions or pretrained reward models built on large-scale da…
Imitation learning addresses the challenge of learning by observing an expert’s demonstrations without access to reward signals from environments. Most existing imitation learning methods that do not require interacting with environments either model the expert distribution as the conditional probab…
In the task of action segmentation, the goal is to partition a lengthy, untrimmed video into a series of action segments. Recently, Transformer-based methods have outperformed the previous temporal convolutional networks (TCNs) in terms of overall performance. However, both TCNs and Transformers enc…