4 citations · 13 across the 20 of their papers we have counts for
9 papers · 1 filter
Towards Multi-Modal Animal Pose Estimation: A Survey and In-Depth Analysis
Qianyi Deng, Oishi Deb, Amir Patel +4
Animal pose estimation (APE) aims to locate the animal body parts using a diverse array of sensor and modality inputs (e.g. RGB cameras, LiDAR, infrared, IMU, acoustic and language…
MambaLoc: Efficient Camera Localisation via State Space Model
Jialu Wang, Kaichen Zhou, Andrew Markham +1
Location information is pivotal for the automation and intelligence of terminal devices and edge-cloud IoT systems, such as autonomous vehicles and augmented reality. However, achi…
SPEAR: Receiver-to-Receiver Acoustic Neural Warping Field
Yuhang He, Shitong Xu, Jia-Xing Zhong +3
We present SPEAR, a continuous receiver-to-receiver acoustic neural warping field for spatial acoustic effects prediction in an acoustic 3D space with a single stationary audio sou…
Pre-training Feature Guided Diffusion Model for Speech Enhancement
Yiyuan Yang, Niki Trigoni, Andrew Markham
Speech enhancement significantly improves the clarity and intelligibility of speech in noisy environments, improving communication and listening experiences. In this paper, we intr…
ZeST: Zero-Shot Material Transfer from a Single Image
Ta-Ying Cheng, Prafull Sharma, Andrew Markham +2
We propose ZeST, a method for zero-shot material transfer to an object in the input image given a material exemplar image. ZeST leverages existing diffusion adapters to extract imp…
WSCLoc: Weakly-Supervised Sparse-View Camera Relocalization
Jialu Wang, Kaichen Zhou, Andrew Markham +1
Despite the advancements in deep learning for camera relocalization tasks, obtaining ground truth pose labels required for the training process remains a costly endeavor. While cur…
SpatialPIN: Enhancing Spatial Reasoning Capabilities of Vision-Language Models through Prompting and Interacting 3D Priors
Chenyang Ma, Kai Lu, Ta-Ying Cheng +2
Current state-of-the-art spatial reasoning-enhanced VLMs are trained to excel at spatial visual question answering (VQA). However, we believe that higher-level 3D-aware tasks, such…
Gen4Gen: Generative Data Pipeline for Generative Multi-Concept Composition
Chun-Hsiao Yeh, Ta-Ying Cheng, He-Yen Hsieh +6
Recent text-to-image diffusion models are able to learn and synthesize images containing novel, personalized concepts (e.g., their own pets or specific items) with just a few examp…
Learning Continuous 3D Words for Text-to-Image Generation
Ta-Ying Cheng, Matheus Gadelha, Thibault Groueix +4
Current controls over diffusion models (e.g., through text or ControlNet) for image generation fall short in recognizing abstract, continuous attributes like illumination direction…