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Found 7 papers, 2 papers with code
Referring Expression Comprehension Using Language Adaptive Inference
Different from universal object detection, referring expression comprehension (REC) aims to locate specific objects referred to by natural language expressions.
MetaGait: Learning to Learn an Omni Sample Adaptive Representation for Gait Recognition
Towards this goal, MetaGait injects meta-knowledge, which could guide the model to perceive sample-specific properties, into the calibration network of the attention mechanism to improve the adaptiveness from the omni-scale, omni-dimension, and omni-process perspectives.
GaitGCI: Generative Counterfactual Intervention for Gait Recognition
Gait is one of the most promising biometrics that aims to identify pedestrians from their walking patterns.
Language Adaptive Weight Generation for Multi-task Visual Grounding
The active perception can take expressions as priors to extract relevant visual features, which can effectively alleviate the mismatches.
GaitMPL: Gait Recognition with Memory-Augmented Progressive Learning
In this work, we propose to solve the hard sample issue with a Memory-augmented Progressive Learning network (GaitMPL), including Dynamic Reweighting Progressive Learning module (DRPL) and Global Structure-Aligned Memory bank (GSAM).
VersatileGait: A Large-Scale Synthetic Gait Dataset Towards in-the-Wild Simulation
To diversify the extrinsic factors of gait, we build a complicated scene with a dense camera layout.
VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios
With the motivation of practical gait recognition applications, we propose to automatically create a large-scale synthetic gait dataset (called VersatileGait) by a game engine, which consists of around one million silhouette sequences of 11, 000 subjects with fine-grained attributes in various complicated scenarios.
