Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …

The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

Whole-body pose estimation localizes the human body, hand, face, and foot keypoints in an
image. This task is challenging due to multi-scale body parts, fine-grained localization for …

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 …

Human motion prediction is a classical problem in computer vision and computer graphics,
which has a wide range of practical applications. Previous effects achieve great empirical …

Sora's high-motion intensity and long consistent videos have significantly impacted the field
of video generation, attracting unprecedented attention. However, existing publicly available …

Human motion generation, a cornerstone technique in animation and video production, has
widespread applications in various tasks like text-to-motion and music-to-dance. Previous …

We present a novel approach for generating 360-degree high-quality, spatiotemporally
coherent human videos from a single image. Our framework combines the strengths of …

One of the primary challenges in the field of human activity recognition (HAR) is the lack of
large labeled datasets. This hinders the development of robust and generalizable models …

Traditional approaches in physics-based motion generation centered around imitation
learning and reward shaping often struggle to adapt to new scenarios. To tackle this …