Search Results for author:
Found 14 papers, 8 papers with code
ARMO: Autoregressive Rigging for Multi-Category Objects
Leveraging this rich dataset, we propose ARMO, a novel rigging framework that utilizes an autoregressive model to predict both joint positions and connectivity relationships in a unified manner.
MOAT: Evaluating LMMs for Capability Integration and Instruction Grounding
However, there remains a significant gap between state-of-the-art LMMs and human performance when it comes to complex tasks that require a combination of fundamental VL capabilities, as well as tasks involving the grounding of complex instructions.
DRiVE: Diffusion-based Rigging Empowers Generation of Versatile and Expressive Characters
Recent advances in generative models have enabled high-quality 3D character reconstruction from multi-modal.
SRIF: Semantic Shape Registration Empowered by Diffusion-based Image Morphing and Flow Estimation
In this paper, we propose SRIF, a novel Semantic shape Registration framework based on diffusion-based Image morphing and Flow estimation.
Combo: Co-speech holistic 3D human motion generation and efficient customizable adaptation in harmony
For the former, we propose to pre-train on data regarding a fixed identity with neutral emotion, and defer the incorporation of customizable conditions (identity and emotion) to fine-tuning stage, which is boosted by our novel X-Adapter for parameter-efficient fine-tuning.
Beyond Talking -- Generating Holistic 3D Human Dyadic Motion for Communication
Furthermore, we introduce the HoCo holistic communication dataset, which is a valuable resource for future research.
FaceChain-ImagineID: Freely Crafting High-Fidelity Diverse Talking Faces from Disentangled Audio
In this paper, we abstract the process of people hearing speech, extracting meaningful cues, and creating various dynamically audio-consistent talking faces, termed Listening and Imagining, into the task of high-fidelity diverse talking faces generation from a single audio.
OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models
Information Technology (IT) Operations (Ops), particularly Artificial Intelligence for IT Operations (AIOps), is the guarantee for maintaining the orderly and stable operation of existing information systems.
Spatially and Spectrally Consistent Deep Functional Maps
We first justify that under certain conditions, the learned maps, when represented in the spectral domain, are already cycle consistent.
Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge
The best-performing algorithms successfully generalized to holdout external validation sets, achieving a median DSC of 89. 5\%, 90. 9\%, and 88. 3\% on North American, European, and Asian cohorts, respectively.
Neural Intrinsic Embedding for Non-rigid Point Cloud Matching
As a primitive 3D data representation, point clouds are prevailing in 3D sensing, yet short of intrinsic structural information of the underlying objects.
Anatomical Invariance Modeling and Semantic Alignment for Self-supervised Learning in 3D Medical Image Analysis
Alice introduces a new contrastive learning strategy which encourages the similarity between views that are diversely mined but with consistent high-level semantics, in order to learn invariant anatomical features.
AuE-IPA: An AU Engagement Based Infant Pain Assessment Method
Recent studies have found that pain in infancy has a significant impact on infant development, including psychological problems, possible brain injury, and pain sensitivity in adulthood.
Attention Based Relation Network for Facial Action Units Recognition
In this paper, we propose a novel Attention Based Relation Network (ABRNet) for AU recognition, which can automatically capture AU relations without unnecessary or even disturbing predefined rules.
