24 accepted papers
Advertising images significantly impact commercial conversion rates and brand equity, yet current evaluation methods rely on subjective judgments, lacking scalability, standardized criteria, and interpretability. To address these challenges, we present **A3 (Advertising Aesthetic Assessment)**, a co
Video quality assessment (VQA) seeks to predict the perceptual quality of a video in alignment with human visual perception, serving as a fundamental tool for quantifying quality degradation across video processing workflows. The dominant VQA paradigm relies on supervised training with human-labeled
Embodied AI has developed rapidly in recent years, but it is still mainly deployed in laboratories, with various distortions in the Real-world limiting its application. Traditionally, Image Quality Assessment (IQA) methods are applied to predict human preferences for distorted images; however, there…
With the rapid integration of large language models (LLMs) into medical decision-support aids, ensuring reliability in reasoning steps—not just final answers—is increasingly critical. Two key safety dimensions are Chain-of-Thought (CoT) faithfulness, which assesses alignment of the model’s reasoning
In the rapidly evolving landscape of Multimodal Large Language Models (MLLMs), the safety concerns of their outputs have earned significant attention. Although numerous datasets have been proposed, they may become outdated with MLLM advancements and are susceptible to data contamination issues. To a
The success of large language models (LLMs) in scientific domains has heightened safety concerns, prompting numerous benchmarks to evaluate their scientific safety. Existing benchmarks often suffer from limited risk coverage and a reliance on subjective evaluation. To address thess problems, we intr…
Video quality assessment (VQA) aims to objectively quantify perceptual quality degradation in alignment with human visual perception. Despite recent advances, existing VQA models still suffer from two critical limitations: poor generalization to out-of-distribution (OOD) videos and limited explainab
We introduce Lumina-Image 2.0, an advanced text-to-image (T2I) model that surpasses previous state-of-the-art methods across multiple benchmarks. Lumina-Image 2.0 is characterized by two key features: (1) Unification - it adopts a unified architecture (Unified Next-DiT) that treats text and image to…
Lumina-T2X is a nascent family of Flow-based Large Diffusion Transformers (Flag-DiT) that establishes a unified framework for transforming noise into various modalities, such as images and videos, conditioned on text instructions. Despite its promising capabilities, Lumina-T2X still encounters chall…
Soft pneumatic actuators (SPAs), due to their compliance and adaptiveness, are promising solutions for manipulation. However, most SPAs have only simple motion modes and cannot perform the compound motion required for complex manipulation. In this letter, we propose a parallel-chamber actuator capab
To reduce the reliance on large-scale datasets recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot segmentation methods first pre-train models on 'seen' classes and then evaluate their generalization performance on 'unseen' classes. However the prior pre-training stage n…
Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently reconstruct the 3D geometry and reflectance of a scene from multi-v…
Anthropomorphic robotic hands have been widely investigated to dexterously manipulate objects because of their anatomical similarity to the human hand. However, the large dimension of configuration space challenges the real-time performance of existing grasp planning methods and drastically limits t
The popularity of Contrastive Language-Image Pre-training (CLIP) has propelled its application to diverse downstream vision tasks. To improve its capacity on downstream tasks, few-shot learning has become a widely-adopted technique. However, existing methods either exhibit limited performance or suf…
Large-scale pre-trained models have shown promising open-world performance for both vision and language tasks. However, their transferred capacity on 3D point clouds is still limited and only constrained to the classification task. In this paper, we first collaborate CLIP and GPT to be a unified 3D…
This paper proposes a perception-shared and swarm trajectory global optimal (STGO) algorithm fused UAVs formation motion planning framework aided by an active sensing system. First, the point cloud received by each UAV is fit by the gaussian mixture model (GMM) and transmitted in the swarm. Resampli…
In this letter, we propose a new class of soft pneumatic linear actuators with single-material, uniaxial deformation, high energy density, and scalability, purely based on periodic curved air channels. The shape of channels is implicitly parameterized by modified triply periodic minimal surfaces (mT
Quadrotor with active sensing was proposed recently to overcome the view field limitation and achieved an excellent perception ability in obstacle avoidance tasks. To realize high-speed flights of this quadrotor in unknown and cluttered environments, a computationally efficient trajectory planner is
Twisting motion plays an important role in kinematics of soft robots. However, current twisting actuators usually suffer from complex mechanical design with multiple materials and undesired coupling with bending and stretching motions. In this letter, we propose a new class of soft twisting pneumati
Shape morphing is at the core of future research, which shows promise for wide applications ranging from reconfigurable electronics to soft material robots. In this paper, we present a novel buckling-induced mechanism for shape morphing using dielectric elastomer actuators (DEAs), by bonding the pla…
Fruitful developments on continuum robots have been witnessed in recent years due to their movements and manipulation capabilities in confined spaces. Due to the nature that a continuum robot has an infinite number of DoFs (Degrees of Freedom), majority of the existing systems deployed abundant actu…
Snake-like manipulators can navigate and perform manipulation in confined spaces. Their recent implementations in surgical robots attracted a lot of attentions. These slender manipulators usually possess either a hyper-redundant articulated vertebrate structure or a continuum one. Primary design con…
Substantial progresses have been made in building versatile anthropomorphic prosthetic hands in the past two decades using emerging technologies. However the trade-offs between functionality, reliability, affordability, appearance, etc. have not been fully settled. Many existing designs, particularl…
This paper presents a trajectory tracking control strategy based on the subspace stabilization approach to accurately manipulate an under-actuated flying robot from a known initial state to the desired terminal state. To facilitate the development of this tracking strategy, the dynamical model of th…