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Found 11 papers, 4 papers with code
Part-aware Shape Generation with Latent 3D Diffusion of Neural Voxel Fields
This paper presents a novel latent 3D diffusion model for the generation of neural voxel fields, aiming to achieve accurate part-aware structures.
Exploring the Distinctiveness and Fidelity of the Descriptions Generated by Large Vision-Language Models
Large Vision-Language Models (LVLMs) are gaining traction for their remarkable ability to process and integrate visual and textual data.
DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Prediction
In Multiple Object Tracking, objects often exhibit non-linear motion of acceleration and deceleration, with irregular direction changes.
DiffusionEdge: Diffusion Probabilistic Model for Crisp Edge Detection
With the recent success of the diffusion probabilistic model (DPM), we found it is especially suitable for accurate and crisp edge detection since the denoising process is directly applied to the original image size.
Manipulating the Label Space for In-Context Classification
Specifically, using our approach on ImageNet, we increase accuracy from 74. 70\% in a 4-shot setting to 76. 21\% with just 2 shots.
DeepFracture: A Generative Approach for Predicting Brittle Fractures
To effectively integrate collision conditions and fractured shapes into a deep learning framework, we introduce the concept of latent impulse representation and geometrically-segmented signed distance function (GS-SDF).
Decoupled Diffusion Models: Simultaneous Image to Zero and Zero to Noise
We propose decoupled diffusion models (DDMs) for high-quality (un)conditioned image generation in less than 10 function evaluations.
DPIT: Dual-Pipeline Integrated Transformer for Human Pose Estimation
Human pose estimation aims to figure out the keypoints of all people in different scenes.
Ranked #22 on
Pose Estimation
on COCO test-dev
Efficient VVC Intra Prediction Based on Deep Feature Fusion and Probability Estimation
The ever-growing multimedia traffic has underscored the importance of effective multimedia codecs.
CaCo: Both Positive and Negative Samples are Directly Learnable via Cooperative-adversarial Contrastive Learning
It trains an encoder by distinguishing positive samples from negative ones given query anchors.
Ranked #65 on
Self-Supervised Image Classification
on ImageNet
Neural Architecture Search for Joint Human Parsing and Pose Estimation
With the spirit of NAS, we propose to search for an efficient network architecture (NPPNet) to tackle two tasks at the same time.
