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Found 7 papers, 0 papers with code
Hierarchical Semantic Correspondence Networks for Video Paragraph Grounding
Specifically, we develop a hierarchical encoder that encodes the multi-modal inputs into semantics-aligned representations at different levels.
Collaborative Static and Dynamic Vision-Language Streams for Spatio-Temporal Video Grounding
The static stream performs cross-modal understanding in a single frame and learns to attend to the target object spatially according to intra-frame visual cues like object appearances.
STVGFormer: Spatio-Temporal Video Grounding with Static-Dynamic Cross-Modal Understanding
The static branch performs cross-modal understanding in a single frame and learns to localize the target object spatially according to intra-frame visual cues like object appearances.
Ranked #2 on
Spatio-Temporal Video Grounding
on HC-STVG2
Action-guided 3D Human Motion Prediction
The ability of forecasting future human motion is important for human-machine interaction systems to understand human behaviors and make interaction.
Augmented 2D-TAN: A Two-stage Approach for Human-centric Spatio-Temporal Video Grounding
We propose an effective two-stage approach to tackle the problem of language-based Human-centric Spatio-Temporal Video Grounding (HC-STVG) task.
Density-aware Haze Image Synthesis by Self-Supervised Content-Style Disentanglement
The key procedure of haze image translation through adversarial training lies in the disentanglement between the feature only involved in haze synthesis, i. e. style feature, and the feature representing the invariant semantic content, i. e. content feature.
Predictive Feature Learning for Future Segmentation Prediction
In the latent feature learned by the autoencoder, global structures are enhanced and local details are suppressed so that it is more predictive.
