24 citations · 63 across the 10 of their papers we have counts for
9 papers · 1 filter
Text Proxy: Decomposing Retrieval from a 1-to-N Relationship into N 1-to-1 Relationships for Text-Video Retrieval
Jian Xiao, Zhenzhen Hu, Jia Li +1
Text-video retrieval (TVR) has seen substantial advancements in recent years, fueled by the utilization of pre-trained models and large language models (LLMs). Despite these advanc…
Static for Dynamic: Towards a Deeper Understanding of Dynamic Facial Expressions Using Static Expression Data
Yin Chen, Jia Li, Yu Zhang +4
Dynamic facial expression recognition (DFER) infers emotions from the temporal evolution of expressions, unlike static facial expression recognition (SFER), which relies solely on…
Seeing is Believing? Enhancing Vision-Language Navigation using Visual Perturbations
Xuesong Zhang, Jia Li, Yunbo Xu +2
Autonomous navigation guided by natural language instructions in embodied environments remains a challenge for vision-language navigation (VLN) agents. Although recent advancements…
Grid Jigsaw Representation with CLIP: A New Perspective on Image Clustering
Zijie Song, Zhenzhen Hu, Richang Hong
Unsupervised representation learning for image clustering is essential in computer vision. Although the advancement of visual models has improved image clustering with efficient vi…
Embedded Heterogeneous Attention Transformer for Cross-lingual Image Captioning
Zijie Song, Zhenzhen Hu, Yuanen Zhou +3
Cross-lingual image captioning is a challenging task that requires addressing both cross-lingual and cross-modal obstacles in multimedia analysis. The crucial issue in this task is…
Image Captioning via Compact Bidirectional Architecture
Zijie Song, Yuanen Zhou, Zhenzhen Hu +4
Most current image captioning models typically generate captions from left-to-right. This unidirectional property makes them can only leverage past context but not future context.…
Semi-Autoregressive Transformer for Image Captioning
Yuanen Zhou, Yong Zhang, Zhenzhen Hu +1
Current state-of-the-art image captioning models adopt autoregressive decoders, \ie they generate each word by conditioning on previously generated words, which leads to heavy late…
More Grounded Image Captioning by Distilling Image-Text Matching Model
Yuanen Zhou, Meng Wang, Daqing Liu +2
Visual attention not only improves the performance of image captioners, but also serves as a visual interpretation to qualitatively measure the caption rationality and model transp…
Quality-aware Unpaired Image-to-Image Translation
Lei Chen, Le Wu, Zhenzhen Hu +1
Generative Adversarial Networks (GANs) have been widely used for the image-to-image translation task. While these models rely heavily on the labeled image pairs, recently some GAN…