Sight and hearing are two senses that play a vital role in human communication and scene
understanding. To mimic human perception ability, audio-visual learning, aimed at …

Visual representation learning is ubiquitous in various real-world applications, including
visual comprehension, video understanding, multi-modal analysis, human-computer …

Recently, deepfakes have raised severe concerns about the authenticity of online media.
Prior works for deepfake detection have made many efforts to capture the intra-modal …

State-of-the-art deep learning models are often trained with a large amount of costly labeled
training data. However, requiring exhaustive manual annotations may degrade the model's …

How does audio describe the world around us? In this paper, we propose a method for
generating an image of a scene from sound. Our method addresses the challenges of …

Learning to classify video data from classes not included in the training data, ie video-based
zero-shot learning, is challenging. We conjecture that the natural alignment between the …

Knowledge distillation, which aims to transfer the knowledge learned by a cumbersome
teacher model to a lightweight student model, has become one of the most popular and …

The recent success of the generative model shows that leveraging the multi-modal
embedding space can manipulate an image using text information. However, manipulating …

Weakly-supervised audio-visual violence detection aims to distinguish snippets containing
multimodal violence events with video-level labels. Many prior works perform audio-visual …

Existing knowledge distillation (KD) method normally fixes the weight of the teacher network,
and uses the knowledge from the teacher network to guide the training of the student …