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 …

Skeleton sequence representation learning has shown great advantages for action
recognition due to its promising ability to model human joints and topology. However, the …

Human parsing aims to partition humans in image or video into multiple pixel-level semantic
parts. In the last decade, it has gained significantly increased interest in the computer vision …

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 …

Existing 3D human object interaction (HOI) datasets and models simply align global
descriptions with the long HOI sequence, while lacking a detailed understanding of …

Human-centric Computer Vision Tasks (HCTs) refer to a series of tasks related to the human
body, such as Human Pose Estimation, Pedestrian Tracking, Re-Identification (ReID) …

This work aims to address an advanced keypoint detection problem: how to accurately
detect any keypoints in complex real-world scenarios, which involves massive, messy, and …

Multi-object multi-part scene segmentation is a challenging task whose complexity scales
exponentially with part granularity and number of scene objects. To address the task, we …

Human parsing has attracted considerable research interest due to its broad potential
applications in the computer vision community. In this paper, we explore several useful …

Recent advancements in Multimodal Large Language Models (MLLMs) have greatly
improved their abilities in image understanding. However, these models often struggle with …