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08/22/2023
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts
Cross-scene generalizable NeRF models, which can directly synthesize nov...
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08/11/2023
INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing
An increasing number of researchers are finding use for nth-order gradie...
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06/13/2023
Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Images
The accurate estimation of six degrees-of-freedom (6DoF) object poses is...
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05/30/2023
Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-level Sparsity via Mixture-of-Experts
Computer vision researchers are embracing two promising paradigms: Visio...
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05/25/2023
POPE: 6-DoF Promptable Pose Estimation of Any Object, in Any Scene, with One Reference
Despite the significant progress in six degrees-of-freedom (6DoF) object...
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12/30/2022
Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search
Learning efficient and interpretable policies has been a challenging tas...
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12/03/2022
StegaNeRF: Embedding Invisible Information within Neural Radiance Fields
Recent advances in neural rendering imply a future of widespread visual ...
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11/29/2022
NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views
Virtual reality and augmented reality (XR) bring increasing demand for 3...
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10/26/2022
M^3ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design
Multi-task learning (MTL) encapsulates multiple learned tasks in a singl...
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10/17/2022
Signal Processing for Implicit Neural Representations
Implicit Neural Representations (INRs) encoding continuous multi-media d...
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10/16/2022
Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices
In this paper, we propose a data-model-hardware tri-design framework for...
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09/19/2022
NeRF-SOS: Any-View Self-supervised Object Segmentation from Complex Real-World Scenes
Neural volumetric representations have shown the potential that Multi-la...
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09/15/2022
Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer?
Vision Transformers (ViTs) have proven to be effective, in solving 2D im...
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07/08/2022
Neural Implicit Dictionary via Mixture-of-Expert Training
Representing visual signals by coordinate-based deep fully-connected net...
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07/04/2022
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations
Neural Radiance Field (NeRF) regresses a neural parameterized scene by d...
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04/05/2022
Unified Implicit Neural Stylization
Representing visual signals by implicit representation (e.g., a coordina...
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04/02/2022
SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image
Despite the rapid development of Neural Radiance Field (NeRF), the neces...
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05/15/2021
FloorPlanCAD: A Large-Scale CAD Drawing Dataset for Panoptic Symbol Spotting
Access to large and diverse computer-aided design (CAD) drawings is crit...
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10/17/2020
MeshMVS: Multi-View Stereo Guided Mesh Reconstruction
Deep learning based 3D shape generation methods generally utilize latent...
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12/13/2019
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching
The deep multi-view stereo (MVS) and stereo matching approaches generall...
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05/06/2018
Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network
The need for fast acquisition and automatic analysis of MRI data is grow...
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04/20/2018
Residual-Guide Feature Fusion Network for Single Image Deraining
Single image rain streaks removal is extremely important since rainy ima...
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04/10/2018
A Deep Information Sharing Network for Multi-contrast Compressed Sensing MRI Reconstruction
In multi-contrast magnetic resonance imaging (MRI), compressed sensing t...
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04/04/2018
A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI
Compressed sensing MRI is a classic inverse problem in the field of comp...
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03/27/2018
A Divide-and-Conquer Approach to Compressed Sensing MRI
Compressed sensing (CS) theory assures us that we can accurately reconst...
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03/23/2018
