23 accepted papers
While cooperative perception can overcome the limitations of single-vehicle systems, the practical implementation of vehicle-to-vehicle and vehicle-to-infrastructure systems is often impeded by significant economic barriers. Aerial-ground cooperation (AGC), which pairs ground vehicles with drones, p
Cooperative 3D perception via Vehicle-to-Everything communication is a promising paradigm for enhancing autonomous driving, offering extended sensing horizons and occlusion resolution. However, the practical deployment of existing methods is hindered at long distances by two critical bottlenecks: th
Cooperative perception is critical for autonomous driving, overcoming the inherent limitations of a single vehicle, such as occlusions and constrained fields-of-view. However, current approaches sharing dense Bird
The rock-climbing fish is a benthic organism that can move rapidly and flexibly on rock surfaces in complex underwater environments. Studies have shown that this unique adhesion-sliding movement mechanism of the rock-climbing fish relies on the anisotropic friction exhibited by its sucker structure,
Image-based virtual try-on (VTON) aims to generate a virtual try-on result by transferring an input garment onto a target person's image. However, the scarcity of paired garment-model data makes it challenging for existing meth ods to achieve high generalization and quality in VTON.Also, it limits t…
Engineered skeletal muscle tissue (SMT) is the ideal driving units for achieving fine movements in biosyncretic robots due to their excellent controllability and potentially large driving force. However, the selective stimulation of SMTs continues to pose a significant technical challenge. In this s
Deep learning approaches for marine fog detection and forecasting have outperformed traditional methods, demonstrating significant scientific and practical importance. However, the limited availability of open-source datasets remains a major challenge. Existing datasets, often focused on a single re…
Contrast-enhanced 3D Medical imaging (e.g., CT, MRI) leverages phase sequences to uncover temporal dynamics vital for diagnosing tumors, lesions, and vascular issues. However, current retrieval models primarily focus on spatial features, neglecting phase-specific progression detailed in clinical rep
The well-established modular autonomous driving system is decoupled into different standalone tasks, e.g. perception, prediction and planning, suffering from information loss and error accumulation across modules. In contrast, end-to-end paradigms unify multi-tasks into a fully differentiable framew
Multi-scale learning is central to semantic segmentation. We visualize the effective receptive field (ERF) of canonical multi-scale representations and point out two risks learning them: \textit{scale inadequacy} and \textit{field inactivation}. A novel multi-scale learner, \textbf{varying window at…
In recent years, bio-syncretic robots actuated by living materials have received widespread attention. Among the common living materials, engineered skeletal muscle tissue (eSKT) has been the focus of researchers due to its high contraction force and good controllability. However, the current perfor…
Performance of trimap-free image matting methods is limited when trying to decouple the deterministic and undetermined regions, especially in the scenes where foregrounds are semantically ambiguous, chromaless, or high transmittance. In this paper, we propose a novel framework named Privileged Prior…
The pectoral fins of manta rays are driven by bilateral muscles to generate up-down flapping movements that allow for efficient and flexible swimming. However, current soft underwater biomimetic flapping robots are mostly driven by unilateral muscle actuators, and the pectoral fin can only realize s
The creation of a parameterized stylized character involves careful selection of numerous parameters, also known as the "avatar vectors" that can be interpreted by the avatar engine. Existing unsupervised avatar vector estimation methods that auto-create avatars for users, however, often fail to wor…
Fact verification is an essential tool to mitigate the spread of false information online, which has gained a widespread attention recently. However, a fact verification in the question-answering dialogue is still underexplored. In this paper, we propose a neural network based approach called questi…
In recent years, temporal knowledge graph (TKG) reasoning has received significant attention. Most existing methods assume that all timestamps and corresponding graphs are available during training, which makes it difficult to predict future events. To address this issue, recent works learn to infer…
Internet video delivery has undergone a tremendous explosion of growth over the past few years. However, the quality of video delivery system greatly depends on the Internet bandwidth. Deep Neural Networks (DNNs) are utilized to improve the quality of video delivery recently. These methods divide a…
Recently, context reasoning using image regions beyond local convolution has shown great potential for scene parsing. In this work, we explore how to incorperate the linguistic knowledge to promote context reasoning over image regions by proposing a Graph Interaction unit (GI unit) and a Semantic Co…
Positive and Unlabeled learning (PU learning) aims to build a binary classifier where only positive and unlabeled data are available for classifier training. However, existing PU learning methods all work on a batch learning mode, which cannot deal with the online learning scenarios with sequential…
Bio-syncretic robots made up of living biological systems and electromechanical systems may have the potential excellent performance of natural biological entities. Therefore, the study of the bio-syncretic robots has got lots of attention in recent years. The 3D skeletal muscles have been used wide…
Micro-robots have a great application prospect in the biomedical field due to the feature of small size. To solve the issues of energy supply and bio-compatibility of micro-robots, bio-syncretic micro-robots composed of biological materials and electromechanical systems have been studied widely. The…
Bio-syncretic robots, consisting of living biological materials and traditional electromechanical systems, have attracted lots of attention due to the potentialities of self-sensing, self-actuation and self-repairing with intrinsic safety and high energy conversion efficiency. However, most of curre…
Cellular mechanical properties as the main physical performance characteristics have been actively studied in the past years for the study of cytobiology and the development of medicine. In this study, by combining Hertz model, a novel strategy is proposed to simultaneously measure the cellular mech…