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Found 6 papers, 0 papers with code
Diffusion Reward: Learning Rewards via Conditional Video Diffusion
Learning rewards from expert videos offers an affordable and effective solution to specify the intended behaviors for reinforcement learning tasks.
Graph-Collaborated Auto-Encoder Hashing for Multi-view Binary Clustering
To address the above issues, we propose a hashing algorithm based on auto-encoders for multi-view binary clustering, which dynamically learns affinity graphs with low-rank constraints and adopts collaboratively learning between auto-encoders and affinity graphs to learn a unified binary code, called Graph-Collaborated Auto-Encoder Hashing for Multi-view Binary Clustering (GCAE).
Discriminative Feature and Dictionary Learning with Part-aware Model for Vehicle Re-identification
In TCPM, triplet-center loss is introduced to ensure each part of vehicle features extracted has intra-class consistency and inter-class separability.
Attribute-guided Feature Learning Network for Vehicle Re-identification
Specially, an attribute-guided module is proposed in AGNet to generate the attribute mask which could inversely guide to select discriminative features for category classification.
Eliminating cross-camera bias for vehicle re-identification
Vehicle re-identification (reID) often requires recognize a target vehicle in large datasets captured from multi-cameras.
Graph-based Multi-view Binary Learning for Image Clustering
To address these problems, we propose a novel binary code algorithm for clustering, which adopts graph embedding to preserve the original data structure, called (Graph-based Multi-view Binary Learning) GMBL in this paper.
