Search Results for author:
Found 9 papers, 5 papers with code
Image-Text Co-Decomposition for Text-Supervised Semantic Segmentation
This paper addresses text-supervised semantic segmentation, aiming to learn a model capable of segmenting arbitrary visual concepts within images by using only image-text pairs without dense annotations.
Learning Continuous Exposure Value Representations for Single-Image HDR Reconstruction
To address this, we propose the continuous exposure value representation (CEVR), which uses an implicit function to generate LDR images with arbitrary EVs, including those unseen during training.
Monocular Quasi-Dense 3D Object Tracking
Experiments on our proposed simulation data and real-world benchmarks, including KITTI, nuScenes, and Waymo datasets, show that our tracking framework offers robust object association and tracking on urban-driving scenarios.
Ranked #7 on
Multiple Object Tracking
on KITTI Tracking test
3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization
The complementary characteristics of active and passive depth sensing techniques motivate the fusion of the Li-DAR sensor and stereo camera for improved depth perception.
Joint Monocular 3D Vehicle Detection and Tracking
The framework can not only associate detections of vehicles in motion over time, but also estimate their complete 3D bounding box information from a sequence of 2D images captured on a moving platform.
Ranked #12 on
Multiple Object Tracking
on KITTI Tracking test
Self-Supervised Learning of Depth and Camera Motion from 360° Videos
We propose a novel self-supervised learning approach for predicting the omnidirectional depth and camera motion from a 360{\deg} video.
Self-view Grounding Given a Narrated 360° Video
The negative log reconstruction loss of the reverse sentence (referred to as "irrelevant loss") is jointly minimized to encourage the reverse sentence to be different from the given sentence.
Deep 360 Pilot: Learning a Deep Agent for Piloting Through 360deg Sports Videos
Given the main object and previously selected viewing angles, our method regresses a shift in viewing angle to move to the next one.
Deep 360 Pilot: Learning a Deep Agent for Piloting through 360° Sports Video
Watching a 360{\deg} sports video requires a viewer to continuously select a viewing angle, either through a sequence of mouse clicks or head movements.
