3 citations · 3 across the 4 of their papers we have counts for
5 papers · 1 filter
Compositional Feature Augmentation for Unbiased Scene Graph Generation
Lin Li, Guikun Chen, Jun Xiao +3
Scene Graph Generation (SGG) aims to detect all the visual relation triplets \texttt{sub}, \texttt{pred}, \texttt{obj} in a given image. With the emergence of various advance…
Ca2-VDM: Efficient Autoregressive Video Diffusion Model with Causal Generation and Cache Sharing
Kaifeng Gao, Jiaxin Shi, Hanwang Zhang +3
With the advance of diffusion models, today's video generation has achieved impressive quality. To extend the generation length and facilitate real-world applications, a majority o…
ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models
Kaifeng Gao, Jiaxin Shi, Hanwang Zhang +2
With the advance of diffusion models, today's video generation has achieved impressive quality. But generating temporal consistent long videos is still challenging. A majority of v…
: Discrete Diffusion Model for Occluded 3D Human Pose Estimation
Weiquan Wang, Jun Xiao, Chunping Wang +3
Continuous diffusion models have demonstrated their effectiveness in addressing the inherent uncertainty and indeterminacy in monocular 3D human pose estimation (HPE). Despite thei…
Seeing Beyond Classes: Zero-Shot Grounded Situation Recognition via Language Explainer
Jiaming Lei, Lin Li, Chunping Wang +2
Benefiting from strong generalization ability, pre-trained vision language models (VLMs), e.g., CLIP, have been widely utilized in zero-shot scene understanding. Unlike simple reco…