This workshop explores the intersection of Computer Vision and NLP, focusing on joint vision-language understanding. Recent advances, particularly in large-scale multimodal pretraining with transformers, have driven progress in various tasks. Topics include visual-linguistic representation learning, VQA, captioning, visual dialog, referring expressions, vision-and-language navigation, embodied QA, and text-to-image generation. We emphasize joint video-language understanding due to its unique challenges. Additionally, we welcome critical work on dataset and algorithmic bias, generalization issues, and efforts toward transparency and explainability.