47 citations · 59 across the 5 of their papers we have counts for
5 papers
Animated Stickers: Bringing Stickers to Life with Video Diffusion
David Yan, Winnie Zhang, Luxin Zhang +15
We introduce animated stickers, a video diffusion model which generates an animation conditioned on a text prompt and static sticker image. Our model is built on top of the state-o…
Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression
Animesh Sinha, Bo Sun, Anmol Kalia +14
We introduce Style Tailoring, a recipe to finetune Latent Diffusion Models (LDMs) in a distinct domain with high visual quality, prompt alignment and scene diversity. We choose sti…
IMU2CLIP: Multimodal Contrastive Learning for IMU Motion Sensors from Egocentric Videos and Text
Seungwhan Moon, Andrea Madotto, Zhaojiang Lin +4
We present IMU2CLIP, a novel pre-training approach to align Inertial Measurement Unit (IMU) motion sensor recordings with video and text, by projecting them into the joint represen…
Connecting What to Say With Where to Look by Modeling Human Attention Traces
Zihang Meng, Licheng Yu, Ning Zhang +4
We introduce a unified framework to jointly model images, text, and human attention traces. Our work is built on top of the recent Localized Narratives annotation framework [30], w…
What's the Point: Semantic Segmentation with Point Supervision
Amy Bearman, Olga Russakovsky, Vittorio Ferrari +1
The semantic image segmentation task presents a trade-off between test time accuracy and training-time annotation cost. Detailed per-pixel annotations enable training accurate mode…