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Found 12 papers, 4 papers with code
GAN-based Garment Generation Using Sewing Pattern Images
The generation of realistic apparel model has become increasingly popular as a result of the rapid pace of change in fashion trends and the growing need for garment models in various applications such as virtual try-on.
SHARE: Single-view Human Adversarial REconstruction
We perform a comprehensive analysis on the impact of camera poses on HPS reconstruction outcomes.
VLAP: Efficient Video-Language Alignment via Frame Prompting and Distilling for Video Question Answering
Our VLAP model addresses both efficient frame sampling and effective cross-modal alignment in a unified way.
Ranked #1 on
Video Question Answering
on STAR Benchmark
MeSa: Masked, Geometric, and Supervised Pre-training for Monocular Depth Estimation
Furthermore, via experiments on the NYUv2 and IBims-1 datasets, we demonstrate that these enhanced representations translate to performance improvements in both the in-distribution and out-of-distribution settings.
Ranked #9 on
Monocular Depth Estimation
on NYU-Depth V2
ICAR: Image-based Complementary Auto Reasoning
Based on this notion, we propose a compatibility learning framework, a category-aware Flexible Bidirectional Transformer (FBT), for visual "scene-based set compatibility reasoning" with the cross-domain visual similarity input and auto-regressive complementary item generation.
Differentiable Simulation of Soft Multi-body Systems
We present a method for differentiable simulation of soft articulated bodies.
Efficient Differentiable Simulation of Articulated Bodies
We derive the gradients of the forward dynamics using spatial algebra and the adjoint method.
Scalable Differentiable Physics for Learning and Control
Differentiable physics is a powerful approach to learning and control problems that involve physical objects and environments.
Differentiable Physics Simulation
Differentiable physics simulation is a powerful family of new techniques that applies gradient-based methods to learning and control of physical systems.
Differentiable Cloth Simulation for Inverse Problems
We propose a differentiable cloth simulator that can be embedded as a layer in deep neural networks.
Shape-Aware Human Pose and Shape Reconstruction Using Multi-View Images
We propose a scalable neural network framework to reconstruct the 3D mesh of a human body from multi-view images, in the subspace of the SMPL model.
Ranked #102 on
3D Human Pose Estimation
on Human3.6M
Learning-Based Cloth Material Recovery From Video
To extract information about the cloth, our method characterizes both the motion space and the visual appearance of the cloth geometry.
