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Found 4 papers, 0 papers with code
3DMiner: Discovering Shapes from Large-Scale Unannotated Image Datasets
We present 3DMiner -- a pipeline for mining 3D shapes from challenging large-scale unannotated image datasets.
GRIP: Generating Interaction Poses Using Spatial Cues and Latent Consistency
In contrast, we introduce GRIP, a learning-based method that takes, as input, the 3D motion of the body and the object, and synthesizes realistic motion for both hands before, during, and after object interaction.
GAIT: Generating Aesthetic Indoor Tours with Deep Reinforcement Learning
Placing and orienting a camera to compose aesthetically meaningful shots of a scene is not only a key objective in real-world photography and cinematography but also for virtual content creation.
Self-Supervised Learning of Motion-Informed Latents
Our goal is to show that common Siamese networks can effectively be trained on video sequences to disentangle attributes related to pose and motion that are useful for video and non-video tasks, yet typically suppressed in usual training schemes.
