Search Results for author:
Found 15 papers, 6 papers with code
Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation
Our model builds a panoptic radiance field representation of any scene from just color images.
FILM: Frame Interpolation for Large Motion
Recent methods use multiple networks to estimate optical flow or depth and a separate network dedicated to frame synthesis.
Ranked #2 on
Video Frame Interpolation
on Xiph-4k
Learning 3D Semantic Segmentation with only 2D Image Supervision
With the recent growth of urban mapping and autonomous driving efforts, there has been an explosion of raw 3D data collected from terrestrial platforms with lidar scanners and color cameras.
Ranked #8 on
LIDAR Semantic Segmentation
on nuScenes
A Step Toward More Inclusive People Annotations for Fairness
In this paper, we present a new set of annotations on a subset of the Open Images dataset called the MIAP (More Inclusive Annotations for People) subset, containing bounding boxes and attributes for all of the people visible in those images.
Virtual Multi-view Fusion for 3D Semantic Segmentation
Features from multiple per view predictions are finally fused on 3D mesh vertices to predict mesh semantic segmentation labels.
Ranked #12 on
Semantic Segmentation
on ScanNet
An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds
We use a U-Net style 3D sparse convolution network to extract features for each frame's LiDAR point-cloud.
Pillar-based Object Detection for Autonomous Driving
We present a simple and flexible object detection framework optimized for autonomous driving.
DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes
In contrast, we propose a general-purpose method that works on both indoor and outdoor scenes.
AVA-ActiveSpeaker: An Audio-Visual Dataset for Active Speaker Detection
The dataset contains temporally labeled face tracks in video, where each face instance is labeled as speaking or not, and whether the speech is audible.
Audio-Visual Active Speaker Detection
speaker-diarization
+2
AVA-Speech: A Densely Labeled Dataset of Speech Activity in Movies
Speech activity detection (or endpointing) is an important processing step for applications such as speech recognition, language identification and speaker diarization.
Sound Audio and Speech Processing
Putting a Face to the Voice: Fusing Audio and Visual Signals Across a Video to Determine Speakers
In this paper, we present a system that associates faces with voices in a video by fusing information from the audio and visual signals.
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
The AVA dataset densely annotates 80 atomic visual actions in 430 15-minute video clips, where actions are localized in space and time, resulting in 1. 58M action labels with multiple labels per person occurring frequently.
Ranked #6 on
Action Detection
on UCF101-24
Egocentric Field-of-View Localization Using First-Person Point-of-View Devices
We present a technique that uses images, videos and sensor data taken from first-person point-of-view devices to perform egocentric field-of-view (FOV) localization.
Pose Embeddings: A Deep Architecture for Learning to Match Human Poses
We present a method for learning an embedding that places images of humans in similar poses nearby.
Understanding Indoor Scenes Using 3D Geometric Phrases
Visual scene understanding is a difficult problem interleaving object detection, geometric reasoning and scene classification.
Ranked #7 on
Room Layout Estimation
on SUN RGB-D
