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 …

The recent wave of AI-generated content has witnessed the great development and success
of Text-to-Image (T2I) technologies. By contrast Text-to-Video (T2V) still falls short of …

Benefiting from masked visual modeling, self-supervised video representation learning has
achieved remarkable progress. However, existing methods focus on learning …

Anomaly detection and localization are widely used in industrial manufacturing for its
efficiency and effectiveness. Anomalies are rare and hard to collect and supervised models …

Contrastive language-image pretraining (CLIP) has demonstrated remarkable success in
various image tasks. However, how to extend CLIP with effective temporal modeling is still …

Abstract Contrastive Language-Image Pretraining (CLIP) has demonstrated impressive zero-
shot learning abilities for image understanding, yet limited effort has been made to …

Existing diffusion-based video editing models have made gorgeous advances for editing
attributes of a source video over time but struggle to manipulate the motion information while …

We propose XVO, a semi-supervised learning method for training generalized monocular
Visual Odometry (VO) models with robust off-the-self operation across diverse datasets and …

Video Transformers have become the prevalent solution for various video downstream tasks
with superior expressive power and flexibility. However these video transformers suffer from …

Video anomaly detection (VAD)–commonly formulated as a multiple-instance learning
problem in a weakly-supervised manner due to its labor-intensive nature–is a challenging …