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Found 40 papers, 20 papers with code
TELA: Text to Layer-wise 3D Clothed Human Generation
Previous works usually encode the human body and clothes as a holistic model and generate the whole model in a single-stage optimization, which makes them struggle for clothing editing and meanwhile lose fine-grained control over the whole generation process.
SemGrasp: Semantic Grasp Generation via Language Aligned Discretization
We introduce a discrete representation that aligns the grasp space with semantic space, enabling the generation of grasp postures in accordance with language instructions.
RAP-SAM: Towards Real-Time All-Purpose Segment Anything
Segment Anything Model (SAM) is one remarkable model that can achieve generalized segmentation.
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generation
We introduce Efficient Motion Diffusion Model (EMDM) for fast and high-quality human motion generation.
Cinematic Behavior Transfer via NeRF-based Differentiable Filming
In the evolving landscape of digital media and video production, the precise manipulation and reproduction of visual elements like camera movements and character actions are highly desired.
InterControl: Generate Human Motion Interactions by Controlling Every Joint
Furthermore, we demonstrate that the distance between joint pairs for human-wise interactions can be generated using an off-the-shelf Large Language Model (LLM).
Unified Human-Scene Interaction via Prompted Chain-of-Contacts
Based on the definition, UniHSI constitutes a Large Language Model (LLM) Planner to translate language prompts into task plans in the form of CoC, and a Unified Controller that turns CoC into uniform task execution.
Synthesizing Physically Plausible Human Motions in 3D Scenes
Experimental results demonstrate that our framework can synthesize physically plausible long-term human motions in complex 3D scenes.
DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Rendering
Realistic human-centric rendering plays a key role in both computer vision and computer graphics.
Systematic Testing of the Data-Poisoning Robustness of KNN
In other words, they cannot falsify the truly-non-robust cases.
Certifying the Fairness of KNN in the Presence of Dataset Bias
We propose a method for certifying the fairness of the classification result of a widely used supervised learning algorithm, the k-nearest neighbors (KNN), under the assumption that the training data may have historical bias caused by systematic mislabeling of samples from a protected minority group.
Controllable Motion Diffusion Model
To enable real-time motion synthesis with diffusion models in response to time-varying control signals, we propose the framework of the Controllable Motion Diffusion Model (COMODO).
Interactive Segment Anything NeRF with Feature Imitation
We propose to imitate the backbone feature of off-the-shelf perception models to achieve zero-shot semantic segmentation with NeRF.
Task-Oriented Human-Object Interactions Generation with Implicit Neural Representations
Generating task-oriented human-object interaction motions in simulation is challenging.
Learning Human Dynamics in Autonomous Driving Scenarios
In this work, we propose a holistic framework for learning physically plausible human dynamics from real driving scenarios, narrowing the gap between real and simulated human behavior in safety-critical applications.
Compressible-composable NeRF via Rank-residual Decomposition
To circumvent the hurdle, in this paper, we present an explicit neural field representation that enables efficient and convenient manipulation of models.
Towards Diverse and Natural Scene-aware 3D Human Motion Synthesis
The ability to synthesize long-term human motion sequences in real-world scenes can facilitate numerous applications.
Fashionformer: A simple, Effective and Unified Baseline for Human Fashion Segmentation and Recognition
This focus on joint human fashion segmentation and attribute recognition.
Point Scene Understanding via Disentangled Instance Mesh Reconstruction
Semantic scene reconstruction from point cloud is an essential and challenging task for 3D scene understanding.
Not All Voxels Are Equal: Semantic Scene Completion from the Point-Voxel Perspective
Firstly, we transfer the voxelized scenes to point clouds by removing these visible empty voxels and adopt a deep point stream to capture semantic information from the scene efficiently.
Ranked #4 on
3D Semantic Scene Completion
on NYUv2
Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements
In this paper, we make the first attempt to reconstruct 3D interacting hands from monocular single RGB images.
Assessing the Performance of Online Students -- New Data, New Approaches, Improved Accuracy
This student performance (SP) modeling problem is a critical step for building adaptive online teaching systems.
Scene-aware Generative Network for Human Motion Synthesis
We revisit human motion synthesis, a task useful in various real world applications, in this paper.
Reinforcement Learning Based Character Controlling
Character controlling is a longstanding problem in understanding the behavior of human.
Group Contextual Encoding for 3D Point Clouds
In this work, we extended the contextual encoding layer that was originally designed for 2D tasks to 3D Point Cloud scenarios.
NeuroDiff: Scalable Differential Verification of Neural Networks using Fine-Grained Approximation
Unfortunately, existing methods either focus on verifying a single network or rely on loose approximations to prove the equivalence of two networks.
Malleable 2.5D Convolution: Learning Receptive Fields along the Depth-axis for RGB-D Scene Parsing
In this paper, we propose a novel operator called malleable 2. 5D convolution to learn the receptive field along the depth-axis.
Ranked #46 on
Semantic Segmentation
on NYU Depth v2
Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
Depth information has proven to be a useful cue in the semantic segmentation of RGB-D images for providing a geometric counterpart to the RGB representation.
Motion Guided 3D Pose Estimation from Videos
We propose a new loss function, called motion loss, for the problem of monocular 3D Human pose estimation from 2D pose.
Ranked #19 on
3D Human Pose Estimation
on Human3.6M
BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation
We propose to treat these spatial details and categorical semantics separately to achieve high accuracy and high efficiency for realtime semantic segmentation.
Ranked #1 on
Real-Time Semantic Segmentation
on COCO-Stuff
Context Prior for Scene Segmentation
Given an input image and corresponding ground truth, Affinity Loss constructs an ideal affinity map to supervise the learning of Context Prior.
Ranked #1 on
Scene Understanding
on ADE20K val
QSW_MPI: a framework for parallel simulation of quantum stochastic walks
QSW_MPI is a python package developed for the modeling of quantum stochastic walks, a generalization of the classical random walk and continuous-time quantum walk in the Lindblad formalism.
Quantum Physics Distributed, Parallel, and Cluster Computing Computational Physics D.1.3; G.4
ReluDiff: Differential Verification of Deep Neural Networks
Existing verification techniques such as Reluplex, ReluVal, and DeepPoly provide formal guarantees, but they are designed for analyzing a single network instead of the relationship between two networks.
Efficient quantum walks over exponentially large sets of combinatorial objects for optimisation
CTQWs form the core mixing operation of a generalised version of the Quantum Approximate Optimisation Algorithm, which works by 'steering' the quantum amplitude into high-quality solutions.
Quantum Physics
An End-to-End Network for Panoptic Segmentation
Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic.
Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors
The weighted nearest neighbors (WNN) estimator has been popularly used as a flexible and easy-to-implement nonparametric tool for mean regression estimation.
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
Semantic segmentation requires both rich spatial information and sizeable receptive field.
Ranked #4 on
Semantic Segmentation
on SkyScapes-Dense
Dichotomous Image Segmentation
Real-Time Semantic Segmentation
+2
Learning a Discriminative Feature Network for Semantic Segmentation
Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction.
Ranked #5 on
Semantic Segmentation
on PASCAL VOC 2012 test
A quantum walk assisted approximate algorithm for bounded NP optimisation problems
This paper describes an application of the Quantum Approximate Optimisation Algorithm (QAOA) to efficiently find approximate solutions for computational problems contained in the polynomially bounded NP optimisation complexity class (NPO PB).
Quantum Physics
Randomness in Deconvolutional Networks for Visual Representation
Toward a deeper understanding on the inner work of deep neural networks, we investigate CNN (convolutional neural network) using DCN (deconvolutional network) and randomization technique, and gain new insights for the intrinsic property of this network architecture.
