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Found 10 papers, 4 papers with code
4D Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenes
We consider the problem of novel view synthesis (NVS) for dynamic scenes.
Clutter Detection and Removal in 3D Scenes with View-Consistent Inpainting
Once clutter is removed, we inpaint geometry and texture in the resulting holes by merging inpainted RGB-D images.
Uni-3D: A Universal Model for Panoptic 3D Scene Reconstruction
Performing holistic 3D scene understanding from a single-view observation, involving generating instance shapes and 3D scene segmentation, is a long-standing challenge.
Self-supervised Neural Articulated Shape and Appearance Models
In addition, our representation enables a large variety of applications, such as few-shot reconstruction, the generation of novel articulations, and novel view-synthesis.
Learning to Infer Semantic Parameters for 3D Shape Editing
Many applications in 3D shape design and augmentation require the ability to make specific edits to an object's semantic parameters (e. g., the pose of a person's arm or the length of an airplane's wing) while preserving as much existing details as possible.
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar
In this work, we depart from visible-wavelength approaches and demonstrate detection, classification, and tracking of hidden objects in large-scale dynamic environments using Doppler radars that can be manufactured at low-cost in series production.
ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition
Furthermore, we propose that weight tensors in networks with proper order and balanced dimension are easier to be compressed.
Exploring Disentangled Feature Representation Beyond Face Identification
This paper proposes learning disentangled but complementary face features with minimal supervision by face identification.
Integral Human Pose Regression
State-of-the-art human pose estimation methods are based on heat map representation.
Ranked #23 on
Pose Estimation
on MPII Human Pose
Recurrent Scale Approximation for Object Detection in CNN
To further increase efficiency and accuracy, we (a): design a scale-forecast network to globally predict potential scales in the image since there is no need to compute maps on all levels of the pyramid.
Ranked #3 on
Face Detection
on Annotated Faces in the Wild
