6 papers
GMOS: Grounding Moving Object Segmentation in 3D Space and Time
Junyu Xie, Tengda Han, Weidi Xie +1
Moving Object Segmentation (MOS) aims to discover, segment, and track objects that move independently of the camera. Current MOS methods, however, exhibit two fundamental limitatio…
Efficiently Reconstructing Dynamic Scenes One D4RT at a Time
Chuhan Zhang, Guillaume Le Moing, Skanda Koppula +11
Understanding and reconstructing the complex geometry and motion of dynamic scenes from video remains a formidable challenge in computer vision. This paper introduces D4RT, a simpl…
More than a Moment: Towards Coherent Sequences of Audio Descriptions
Eshika Khandelwal, Junyu Xie, Tengda Han +5
Audio Descriptions (ADs) convey essential on-screen information, allowing visually impaired audiences to follow videos. To be effective, ADs must form a coherent sequence that help…
Character-Centric Understanding of Animated Movies
Zhongrui Gui, Junyu Xie, Tengda Han +2
Animated movies are captivating for their unique character designs and imaginative storytelling, yet they pose significant challenges for existing recognition systems. Unlike the c…
Shot-by-Shot: Film-Grammar-Aware Training-Free Audio Description Generation
Junyu Xie, Tengda Han, Max Bain +5
Our objective is the automatic generation of Audio Descriptions (ADs) for edited video material, such as movies and TV series. To achieve this, we propose a two-stage framework tha…
FacaDiffy: Inpainting Unseen Facade Parts Using Diffusion Models
Thomas Froech, Olaf Wysocki, Yan Xia +4
High-detail semantic 3D building models are frequently utilized in robotics, geoinformatics, and computer vision. One key aspect of creating such models is employing 2D conflict ma…