The recent wave of AI-generated content (AIGC) has witnessed substantial success in
computer vision, with the diffusion model playing a crucial role in this achievement. Due to …

Large language models have demonstrated impressive universal capabilities across a wide
range of open-ended tasks and have extended their utility to encompass multimodal …

Video moment retrieval pursues an efficient and generalized solution to identify the specific
temporal segments within an untrimmed video that correspond to a given language …

With the burgeoning growth of online video platforms and the escalating volume of video
content, the demand for proficient video understanding tools has intensified markedly. Given …

Most text-driven human motion generation methods employ sequential modeling
approaches, eg, transformer, to extract sentence-level text representations automatically and …

The performance of text-video retrieval has been significantly improved by vision-language
cross-modal learning schemes. The typical solution is to directly align the global video-level …

With the explosive growth of web videos and emerging large-scale vision-language pre-
training models, eg, CLIP, retrieving videos of interest with text instructions has attracted …

Text-video retrieval is a challenging cross-modal task, which aims to align visual entities with
natural language descriptions. Current methods either fail to leverage the local details or are …

Dense contrastive learning (DCL) has been recently explored for learning localized
information for dense prediction tasks (eg, detection and segmentation). It still suffers the …

Image Retrieval aims to retrieve corresponding images based on a given query. In
application scenarios, users intend to express their retrieval intent through various query …