Then we introduce a semantic mapper that produces the proxy masks from various input conditions including semantic masks.

This protocol is often regarded as a "golden compass" for navigating SoT A detectors. But can these stand-out "winners" be

TextDiffuser consists of two stages: first, a Transformer model generates the layout of keywords extracted from text prompts, and then diffusion models generate images conditioned on the text prompt and the generated layout.

Across a wide range of hardware scenarios, the computational efficiency and physical size of the arithmetic units significantly influence the speed and footprint of the overall hardware system.

For example, hats and sunglasses are placed on incorrect objects. We introduce a novel method T oMeto address these challenges.

With the advent of large language models (LLMs), reinforcement learning from human feedback (RLHF) has emerged as a pivotal technological paradigm to align models' behaviors with human values [

Our method's efficacy is demonstrated on the class-conditional ImageNet generation benchmark, where