In this study, we introduce a methodology for human image animation by leveraging a 3D
human parametric model within a latent diffusion framework to enhance shape alignment …

Character Animation aims to generating character videos from still images through driving
signals. Currently diffusion models have become the mainstream in visual generation …

We introduce Grounded SAM, which uses Grounding DINO as an open-set object detector to
combine with the segment anything model (SAM). This integration enables the detection and …

We present MOFA-Video, an advanced controllable image animation method that generates
video from the given image using various additional controllable signals (such as human …

Modeling and rendering photorealistic avatars is of crucial importance in many applications.
Existing methods that build a 3D avatar from visual observations, however, struggle to …

We present Follow-Your-Emoji, a diffusion-based framework for portrait animation, which
animates a reference portrait with target landmark sequences. The main challenge of portrait …

We present Sapiens, a family of models for four fundamental human-centric vision tasks–2D
pose estimation, body-part segmentation, depth estimation, and surface normal prediction …

This paper introduces a novel framework for virtual try-on, termed Wear-Any-Way. Different
from previous methods, Wear-Any-Way is a customizable solution. Besides generating high …

This work proposes an end-to-end neural interactive keypoint detection framework named
Click-Pose, which can significantly reduce more than 10 times labeling costs of 2D keypoint …

In recent years, generative artificial intelligence has achieved significant advancements in
the field of image generation, spawning a variety of applications. However, video generation …