Search Results for author:
Found 14 papers, 4 papers with code
Should All Proposals be Treated Equally in Object Detection?
We formulate this as a learning problem where the goal is to assign operators to proposals, in the detection head, so that the total computational cost is constrained and the precision is maximized.
A Token-level Contrastive Framework for Sign Language Translation
Sign Language Translation (SLT) is a promising technology to bridge the communication gap between the deaf and the hearing people.
Ranked #6 on
Sign Language Translation
on CSL-Daily
The Overlooked Classifier in Human-Object Interaction Recognition
Human-Object Interaction (HOI) recognition is challenging due to two factors: (1) significant imbalance across classes and (2) requiring multiple labels per image.
SA-VQA: Structured Alignment of Visual and Semantic Representations for Visual Question Answering
As a multi-modality task, it is challenging since it requires not only visual and textual understanding, but also the ability to align cross-modality representations.
The Overlooked Classifier in Human-Object Interaction Recognition
Human-Object Interaction (HOI) recognition is challenging due to two factors: (1) significant imbalance across classes and (2) requiring multiple labels per image.
Ranked #1 on
Human-Object Interaction Detection
on HICO
Improving Vision Transformers for Incremental Learning
This paper proposes a working recipe of using Vision Transformer (ViT) in class incremental learning.
Is Object Detection Necessary for Human-Object Interaction Recognition?
This paper revisits human-object interaction (HOI) recognition at image level without using supervisions of object location and human pose.
A Unified Transferable Model for ML-Enhanced DBMS
We propose to explore the transferabilities of the ML methods both across tasks and across DBs to tackle these fundamental drawbacks.
Beating the Standard Quantum Limit under Ambient Conditions with Solid-State Spins
However, it has not been realized in solid-state spin systems at ambient conditions, owing to its intrinsic complexity for the preparation and survival of pure and entangled quantum states.
Quantum Physics
Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
In this work, we show that such adversarial-based methods can only reduce the domain style gap, but cannot address the domain content distribution gap that is shown to be important for object detectors.
Deeply Learned Compositional Models for Human Pose Estimation
This results in a network with a hierarchical compositional architecture and bottom-up/top-down inference stages.
Ranked #11 on
Pose Estimation
on MPII Human Pose
Towards a Unified Compositional Model for Visual Pattern Modeling
Compositional models represent visual patterns as hierarchies of meaningful and reusable parts.
Efficient Online Local Metric Adaptation via Negative Samples for Person Re-Identification
In contrast to these methods, this paper advocates a different paradigm: part of the learning can be performed online but with nominal costs, so as to achieve online metric adaptation for different input probes.
Learning Reconstruction-Based Remote Gaze Estimation
A common treatment is to use the same local reconstruction in the two spaces, i. e., the reconstruction weights in the appearance space are transferred to the gaze space for gaze reconstruction.
