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Found 9 papers, 0 papers with code
CoMo: Controllable Motion Generation through Language Guided Pose Code Editing
Text-to-motion models excel at efficient human motion generation, but existing approaches lack fine-grained controllability over the generation process.
Out-of-Distribution Detection using Neural Activation Prior
Our neural activation prior is based on a key observation that, for a channel before the global pooling layer of a fully trained neural network, the probability of a few neurons being activated with a large response by an in-distribution (ID) sample is significantly higher than that by an OOD sample.
DiffusionPhase: Motion Diffusion in Frequency Domain
In this study, we introduce a learning-based method for generating high-quality human motion sequences from text descriptions (e. g., ``A person walks forward").
TLControl: Trajectory and Language Control for Human Motion Synthesis
Controllable human motion synthesis is essential for applications in AR/VR, gaming, movies, and embodied AI.
TORE: Token Reduction for Efficient Human Mesh Recovery with Transformer
We further demonstrate the generalizability of our method on hand mesh recovery.
Learn to Predict How Humans Manipulate Large-sized Objects from Interactive Motions
We also observe that an object's intrinsic physical properties are useful for the object motion prediction, and thus design a set of object dynamic descriptors to encode such intrinsic properties.
MulayCap: Multi-layer Human Performance Capture Using A Monocular Video Camera
We introduce MulayCap, a novel human performance capture method using a monocular video camera without the need for pre-scanning.
Part Segmentation for Highly Accurate Deformable Tracking in Occlusions via Fully Convolutional Neural Networks
While recent work has shown direct estimation techniques can be quite powerful, geometric tracking methods using point clouds can provide a very high level of 3D accuracy which is necessary for many robotic applications.
Dynamic High Resolution Deformable Articulated Tracking
The last several years have seen significant progress in using depth cameras for tracking articulated objects such as human bodies, hands, and robotic manipulators.
