7 accepted papers
Test-time training (TTT) in transformers is commonly interpreted as a form of online meta-learning that memorizes a key–value mapping at test time. However, our analysis reveals multiple phenomena that contradict this memorization-based interpretation. Motivated by these findings, we revisit the for…
Transformers are increasingly prevalent for multiview computer vision tasks, where geometric relationships between viewpoints are critical for 3D perception. To leverage these relationships, multiview transformers must use camera geometry to ground visual tokens in 3D space. In this work, we compare…
Multi-modal emotion recognition (MER) is crucial for improving human-computer interaction. Convolutional neural networks (CNNs) are the mainstream for MER tasks, but they require large databases, extensive memory, and significant energy, limiting their practical use. This paper proposes a novel MER…
Exoskeleton technology holds significant promise within the human-centric paradigm of Industry 5.0 for mitigating work-related musculoskeletal disorders (WMSDs). However, existing systems often struggle with mismatched assistive torque and inefficient human-machine collaboration under dynamic loadin
Previous research has shown that load-bearing with elastic suspension backpacks improves human biomechanics and reduces human energy expenditure. Constant-force suspension backpacks (CFSB) with zero stiffness were developed to minimize the inertial force of loads. However, there is a mismatch betwee
Preference-based optimizing methods have shown their advantages and potential in exploring individual, comfortable, and effective control strategies and assistance parameters of exoskeletons during locomotion. Research indicates that compared with naive wearers, knowledgeable wearers with abundant e…
Research has indicated that exoskeletons can assist human movement, but due to the influence of additional weight and challenges in control strategy design, only a few exoskeletons effectively reduce the wearers’ metabolic costs during running. This paper proposes an innovative and efficient hip-ass…