We present DetToolChain, a novel prompting paradigm, to unleash the zero-shot object
detection ability of multimodal large language models (MLLMs), such as GPT-4V and …

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) …

Mirroring the practice of human medical experts, the integration of diverse medical
examination modalities enhances the performance of predictive models in clinical settings …

Person/vehicle re‐identification aims to use technologies such as cross‐camera retrieval to
associate the same person (same vehicle) in the surveillance videos at different locations …

Aligning multiple modalities in a latent space, such as images and texts, has shown to
produce powerful semantic visual representations, fueling tasks like image captioning, text …

In recent years, skeleton-based action recognition, leveraging multimodal Graph
Convolutional Networks (GCN), has achieved remarkable results. However, due to their …

We present VisionLLM v2, an end-to-end generalist multimodal large model (MLLM) that
unifies visual perception, understanding, and generation within a single framework. Unlike …

Skeleton-based action recognition is a core task in the field of video understanding.
Skeleton sequences are characterized by high information density, low redundancy, and …

Skeleton-based action recognition, renowned for its computational efficiency and
indifference to lighting variations, has become a focal point in the realm of motion analysis …

Skeleton-based multi-entity action recognition is a challenging task aiming to identify
interactive actions or group activities involving multiple diverse entities. Existing models for …