20 accepted papers
Action Quality Assessment (AQA) aims to score how well an action is performed and is widely used in sports analysis, rehabilitation assessment, and human skill evaluation. Multi-modal AQA has recently achieved strong progress by leveraging complementary visual and kinematic cues, yet real-world depl
Homeostatic mechanisms play a crucial role in maintaining optimal functionality within the neural circuits of the brain. By regulating physiological and biochemical processes, these mechanisms ensure the stability of an organism’s internal environment, enabling it to better adapt to external changes
Referring 3D segmentation seeks to localize and segment target objects in a 3D scene given a natural-language query, requiring joint reasoning over geometric structures and linguistic cues. Although recent progress using 3D Gaussian Splatting (3DGS) has improved rendering quality, existing methods s
Audio is a fundamental modality for analyzing speech, music, and environmental sounds. While pretrained audio models have significantly advanced audio understanding, they remain fragile in real-world scenarios where data distributions evolve over time. In this work, we present the first systematic b…
Functional magnetic resonance imaging (fMRI) provides dynamic measurements of human brain activity at high spatial resolution and depth, but its use is constrained by high cost, limited accessibility, and strict acquisition requirements. Synthesizing fMRI data from more accessible, non-invasive moda…
Single-channel audio separation aims to separate individual sources from a single-channel mixture. Most existing methods rely on supervised learning with synthetically generated paired data. However, obtaining high-quality paired data in real-world scenarios is often difficult. This data scarcity ca
Audio super-resolution (SR), i.e., upsampling the low-resolution (LR) waveform to the high-resolution (HR) version, has recently been explored with diffusion and bridge models, while previous methods often suffer from sub-optimal upsampling quality due to their uninformative generation prior. Toward…
Speech super-resolution (SR), which generates a waveform at a higher sampling rate from its low-resolution version, is a long-standing critical task in speech restoration. Previous works have explored speech SR in different data spaces, but these methods either require additional compression network…
Human Action Recognition (HAR) has widespread applications in areas such as human-computer interaction, elderly care, and home healthcare. However, current sensor-based HAR faces challenges of low fine-grained recognition performance and difficulty in distinguishing similar actions. To solve this pr…
This paper introduces Swap Forward (SaFa), a modality-agnostic and efficient method to generate seamless and coherent long spectrum and panorama using a latent swap joint diffusion process across multi-views. We first investigate spectrum aliasing problem in spectrum-based audio generation caused by…
Contrastive learning has achieved significant progress in the field of self-supervised skeleton-based action recognition. However, existing methods often apply strong augmentations directly to skeleton data, which can distort or even lose the semantic of the skeletons. Additionally, most methods foc…
Text-to-music (TTM) generation, which converts textual descriptions into audio, opens up innovative avenues for multimedia creation. Achieving high quality and diversity in this process demands extensive, high-quality data, which are often scarce in available datasets. Most open-source datasets freq
Respiratory rate (RR) is a critical health indicator often monitored under inconvenient scenarios, limiting its practicality for continuous monitoring. Photoplethysmography (PPG) sensors, increasingly integrated into wearable devices, offer a chance to continuously estimate RR in a portable manner.…
The superior performances of pre-trained foundation models in various visual tasks underscore their potential to enhance the 2D models' open-vocabulary ability. Existing methods explore analogous applications in the 3D space. However, most of them only center around knowledge extraction from singula…
Jumping is a key locomotion for miniature robots, but it is difficult for a robot to jump a long distance without flipping. To solve this problem, we develop a miniature locust-inspired jumping robot, which has a body length of 10 cm and weight of 60 g. On the basis of the extracted skeletal muscle
Graph neural networks have emerged as a leading architecture for many graph-level tasks, such as graph classification and graph generation. As an essential component of the architecture, graph pooling is indispensable for obtaining a holistic graph-level representation of the whole graph. Although…
The standard option framework is developed on the Semi-Markov Decision Process (SMDP) which is unstable to optimize and sample inefficient. To this end, we propose the Hidden Temporal MDP (HiT-MDP) and prove that the option-induced HiT-MDP is homomorphic equivalent to the option-induced SMDP. A nove…
In this paper, we study the problem of safe online learning to re-rank, where user feedback is used to improve the quality of displayed lists. Learning to rank has traditionally been studied in two settings. In the offline setting, rankers are typically learned from relevance labels created by judge…
Social interaction between a robot and rats is important since the robot can generate reproducible social behaviors across trials. However, lacking internal state feedback from the rat makes current robot-rat interaction a very preliminary level comparing with rat-rat interaction. Previous biologica…
The interaction test between a robotic rat and living rat is considered as a possible way to quantitatively characterize the rat sociality. In such robot-rat interactions, the robot should be designed to fully replicate a real rat in terms of morphological and behavioral characteristics. To address…