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Found 7 papers, 3 papers with code
SEEG: Semantic Energized Co-Speech Gesture Generation
Talking gesture generation is a practical yet challenging task which aims to synthesize gestures in line with speech.
Ranked #6 on
Gesture Generation
on TED Gesture Dataset
Divide and Rule: Recurrent Partitioned Network for Dynamic Processes
Differently, our goal is to represent a system with a part-whole hierarchy and discover the implied dependencies among intra-system variables: inferring the interactions that possess causal effects on the sub-system behavior with REcurrent partItioned Network (REIN).
OR-Net: Pointwise Relational Inference for Data Completion under Partial Observation
Specifically, we expect to approximate the real joint distribution over the partial observation and latent variables, thus infer the unseen targets respectively.
Decoupled Spatial Temporal Graphs for Generic Visual Grounding
Visual grounding is a long-lasting problem in vision-language understanding due to its diversity and complexity.
Look, Cast and Mold: Learning 3D Shape Manifold from Single-view Synthetic Data
To generalize the model towards a real scenario, we propose to fulfill several aspects: (1) Look: visually incorporate spatial structure from the single view to enhance the expressiveness of representation; (2) Cast: perceptually align the 2D image features to the 3D shape priors with cross-modal semantic contrastive mapping; (3) Mold: reconstruct stereo-shape of target by transforming embeddings into the desired manifold.
Cascaded Revision Network for Novel Object Captioning
By this novel cascaded captioning-revising mechanism, CRN can accurately describe images with unseen objects.
Attract or Distract: Exploit the Margin of Open Set
In this paper, we exploit the semantic structure of open set data from two aspects: 1) Semantic Categorical Alignment, which aims to achieve good separability of target known classes by categorically aligning the centroid of target with the source.
