Search Results for author:
Found 8 papers, 4 papers with code
CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation
Deep Neural Networks (DNNs) are widely used for visual classification tasks, but their complex computation process and black-box nature hinder decision transparency and interpretability.
UnLoc: A Unified Framework for Video Localization Tasks
While large-scale image-text pretrained models such as CLIP have been used for multiple video-level tasks on trimmed videos, their use for temporal localization in untrimmed videos is still a relatively unexplored task.
Ranked #1 on
Action Segmentation
on COIN
im2nerf: Image to Neural Radiance Field in the Wild
We take a step towards addressing this shortcoming by introducing a model that encodes the input image into a disentangled object representation that contains a code for object shape, a code for object appearance, and an estimated camera pose from which the object image is captured.
Optical Mouse: 3D Mouse Pose From Single-View Video
We present a method to infer the 3D pose of mice, including the limbs and feet, from monocular videos.
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
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.
Speech2Action: Cross-modal Supervision for Action Recognition
We train a BERT-based Speech2Action classifier on over a thousand movie screenplays, to predict action labels from transcribed speech segments.
