13 citations · 16 across the 6 of their papers we have counts for
6 papers
Vibe Spaces for Creatively Connecting and Expressing Visual Concepts
Huzheng Yang, Katherine Xu, Andrew Lu +3
Creating new visual concepts often requires connecting distinct ideas through their most relevant shared attributes -- their vibe. We introduce Vibe Blending, a novel task for gene…
SAM 3: Segment Anything with Concepts
Nicolas Carion, Laura Gustafson, Yuan-Ting Hu +35
We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short…
"I Know It When I See It": Mood Spaces for Connecting and Expressing Visual Concepts
Huzheng Yang, Katherine Xu, Michael D. Grossberg +2
Expressing complex concepts is easy when they can be labeled or quantified, but many ideas are hard to define yet instantly recognizable. We propose a Mood Board, where users conve…
Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models
Katherine Xu, Lingzhi Zhang, Jianbo Shi
Recent advances in text-to-image (T2I) diffusion models have facilitated creative and photorealistic image synthesis. By varying the random seeds, we can generate many images for a…
Detecting Origin Attribution for Text-to-Image Diffusion Models
Katherine Xu, Lingzhi Zhang, Jianbo Shi
Modern text-to-image (T2I) diffusion models can generate images with remarkable realism and creativity. These advancements have sparked research in fake image detection and attribu…
Amodal Completion via Progressive Mixed Context Diffusion
Katherine Xu, Lingzhi Zhang, Jianbo Shi
Our brain can effortlessly recognize objects even when partially hidden from view. Seeing the visible of the hidden is called amodal completion; however, this task remains a challe…