2 citations · 4 across the 8 of their papers we have counts for
8 papers
CASIM: Composite Aware Semantic Injection for Text to Motion Generation
Che-Jui Chang, Qingze Tony Liu, Honglu Zhou +2
Recent advances in generative modeling and tokenization have driven significant progress in text-to-motion generation, leading to enhanced quality and realism in generated motions.…
M3Act: Learning from Synthetic Human Group Activities
Che-Jui Chang, Danrui Li, Deep Patel +7
The study of complex human interactions and group activities has become a focal point in human-centric computer vision. However, progress in related tasks is often hindered by the…
Procedure-Aware Pretraining for Instructional Video Understanding
Honglu Zhou, Roberto Martín-Martín, Mubbasir Kapadia +2
Our goal is to learn a video representation that is useful for downstream procedure understanding tasks in instructional videos. Due to the small amount of available annotations, a…
MSI: Maximize Support-Set Information for Few-Shot Segmentation
Seonghyeon Moon, Samuel S. Sohn, Honglu Zhou +4
FSS(Few-shot segmentation) aims to segment a target class using a small number of labeled images(support set). To extract information relevant to the target class, a dominant appro…
HM: Hybrid Masking for Few-Shot Segmentation
Seonghyeon Moon, Samuel S. Sohn, Honglu Zhou +4
We study few-shot semantic segmentation that aims to segment a target object from a query image when provided with a few annotated support images of the target class. Several recen…
D-HYPR: Harnessing Neighborhood Modeling and Asymmetry Preservation for Digraph Representation Learning
Honglu Zhou, Advith Chegu, Samuel S. Sohn +3
Digraph Representation Learning (DRL) aims to learn representations for directed homogeneous graphs (digraphs). Prior work in DRL is largely constrained (e.g., limited to directed…
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality
Honglu Zhou, Asim Kadav, Aviv Shamsian +6
Group Activity Recognition detects the activity collectively performed by a group of actors, which requires compositional reasoning of actors and objects. We approach the task by m…
Hopper: Multi-hop Transformer for Spatiotemporal Reasoning
Honglu Zhou, Asim Kadav, Farley Lai +4
This paper considers the problem of spatiotemporal object-centric reasoning in videos. Central to our approach is the notion of object permanence, i.e., the ability to reason about…