activity
20172026
most citedDeep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models

71 citations · 212 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2026

Advantage-Guided Gate: Reshaping Open-Ended Reasoning for Vision-Based Spatial Intelligence

Ling Lin, Yang Bai, Congcong Zhu +6

Multimodal large language models (MLLMs) have demonstrated significant potential in complex spatial scene understanding and reasoning tasks. However, their open-ended reasoning pro…

cs.CV2022★ 1 cited

Evolutionary Generalized Zero-Shot Learning

Dubing Chen, Chenyi Jiang, Haofeng Zhang

Attribute-based Zero-Shot Learning (ZSL) has revolutionized the ability of models to recognize new classes not seen during training. However, with the advancement of large-scale mo…

cs.CV2022★ 1 cited

Action Quality Assessment with Temporal Parsing Transformer

Yang Bai, Desen Zhou, Songyang Zhang +5

Action Quality Assessment(AQA) is important for action understanding and resolving the task poses unique challenges due to subtle visual differences. Existing state-of-the-art meth…

cs.CV2021★ 26 cited

Discriminative Latent Semantic Graph for Video Captioning

Yang Bai, Junyan Wang, Yang Long +4

Video captioning aims to automatically generate natural language sentences that can describe the visual contents of a given video. Existing generative models like encoder-decoder f…

cs.LG2021★ 71 cited

Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models

Sam Bond-Taylor, Adam Leach, Yang Long +1

Deep generative models are a class of techniques that train deep neural networks to model the distribution of training samples. Research has fragmented into various interconnected…

cs.CV2020★ 21 cited

Query Twice: Dual Mixture Attention Meta Learning for Video Summarization

Junyan Wang, Yang Bai, Yang Long +4

Video summarization aims to select representative frames to retain high-level information, which is usually solved by predicting the segment-wise importance score via a softmax fun…