research
∙
04/05/2023
Segment Anything
We introduce the Segment Anything (SA) project: a new task, model, and d...
share
research
∙
03/06/2023
Learning Humanoid Locomotion with Transformers
We present a sim-to-real learning-based approach for real-world humanoid...
research
∙
10/06/2022
Real-World Robot Learning with Masked Visual Pre-training
In this work, we explore self-supervised visual pre-training on images f...
research
∙
03/11/2022
Masked Visual Pre-training for Motor Control
This paper shows that self-supervised visual pre-training from real-worl...
research
∙
06/28/2021
Early Convolutions Help Transformers See Better
Vision transformer (ViT) models exhibit substandard optimizability. In p...
research
∙
08/13/2020
What Should Not Be Contrastive in Contrastive Learning
Recent self-supervised contrastive methods have been able to produce imp...
research
∙
06/09/2020
Reducing Class Collapse in Metric Learning with Easy Positive Sampling
Metric learning seeks perceptual embeddings where visually similar insta...
research
∙
12/20/2019
Something-Else: Compositional Action Recognition with Spatial-Temporal Interaction Networks
Human action is naturally compositional: humans can easily recognize and...
research
∙
09/10/2019
Reasoning About Human-Object Interactions Through Dual Attention Networks
Objects are entities we act upon, where the functionality of an object i...
research
∙
07/30/2018
Acquisition of Localization Confidence for Accurate Object Detection
Modern CNN-based object detectors rely on bounding box regression and no...
research
∙
07/26/2018
Unified Perceptual Parsing for Scene Understanding
Humans recognize the visual world at multiple levels: we effortlessly ca...
research
∙
06/27/2018
Learning Visually-Grounded Semantics from Contrastive Adversarial Samples
We study the problem of grounding distributional representations of text...
research
∙
04/30/2018
CrowdHuman: A Benchmark for Detecting Human in a Crowd
Human detection has witnessed impressive progress in recent years. Howev...
research
∙
11/21/2017
Repulsion Loss: Detecting Pedestrians in a Crowd
Detecting individual pedestrians in a crowd remains a challenging proble...
research
∙
11/20/2017
MegDet: A Large Mini-Batch Object Detector
The improvements in recent CNN-based object detection works, from R-CNN ...
research
∙
05/08/2017
