Search Results for author:
Found 28 papers, 9 papers with code
Adaptive As-Natural-As-Possible Image Stitching
Computing the warp is fully automated and uses a combination of local homography and global similarity transformations, both of which are estimated with respect to the target.
Distributed Bundle Adjustment
The runtime of our implementation scales linearly with the number of observed points.
Collaborative Human-AI (CHAI): Evidence-Based Interpretable Melanoma Classification in Dermoscopic Images
Quantitative relevance of results, according to non-expert similarity, as well as localized image regions, are also significantly improved.
A Prior-Less Method for Multi-Face Tracking in Unconstrained Videos
This paper presents a prior-less method for tracking and clustering an unknown number of human faces and maintaining their individual identities in unconstrained videos.
Video Instance Segmentation Tracking With a Modified VAE Architecture
We propose a modified variational autoencoder (VAE) architecture built on top of Mask R-CNN for instance-level video segmentation and tracking.
True-Time-Delay Arrays for Fast Beam Training in Wideband Millimeter-Wave Systems
We also propose a suitable algorithm that requires a single pilot to achieve high-accuracy estimation of angle of arrival.
AR-Net: Adaptive Frame Resolution for Efficient Action Recognition
Specifically, given a video frame, a policy network is used to decide what input resolution should be used for processing by the action recognition model, with the goal of improving both accuracy and efficiency.
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition
Temporal modelling is the key for efficient video action recognition.
VA-RED$^2$: Video Adaptive Redundancy Reduction
An inherent property of real-world videos is the high correlation of information across frames which can translate into redundancy in either temporal or spatial feature maps of the models, or both.
A 4-Element 800MHz-BW 29mW True-Time-Delay Spatial Signal Processor Enabling Fast Beam-Training with Data Communications
In this work, we demonstrate a true-time-delay (TTD) array with digitally reconfigurable delay elements enabling both fast beam-training at the receiver with wideband data communications.
Mutual Information Continuity-constrained Estimator
Accordingly, we propose Mutual Information Continuity-constrained Estimator (MICE).
SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning
Based on this model architecture, we show that video captioning can benefit significantly from more densely sampled video frames as opposed to previous successes with sparsely sampled video frames for video-and-language understanding tasks (e. g., video question answering).
Wideband Beamforming with Rainbow Beam Training using Reconfigurable True-Time-Delay Arrays for Millimeter-Wave Wireless
The decadal research in integrated true-time-delay arrays have seen organic growth enabling realization of wideband beamformers for large arrays with wide aperture widths.
Multi-Mode Spatial Signal Processor with Rainbow-like Fast Beam Training and Wideband Communications using True-Time-Delay Arrays
Initial access in millimeter-wave (mmW) wireless is critical toward successful realization of the fifth-generation (5G) wireless networks and beyond.
Cross-modal Representation Learning for Zero-shot Action Recognition
The model design provides a natural mechanism for visual and semantic representations to be learned in a shared knowledge space, whereby it encourages the learned visual embedding to be discriminative and more semantically consistent.
Ranked #3 on
Zero-Shot Action Recognition
on ActivityNet
LAVENDER: Unifying Video-Language Understanding as Masked Language Modeling
In this work, we explore a unified VidL framework LAVENDER, where Masked Language Modeling (MLM) is used as the common interface for all pre-training and downstream tasks.
MPT: Mesh Pre-Training with Transformers for Human Pose and Mesh Reconstruction
Traditional methods of reconstructing 3D human pose and mesh from single images rely on paired image-mesh datasets, which can be difficult and expensive to obtain.
Ranked #14 on
3D Human Pose Estimation
on 3DPW
Equivariant Similarity for Vision-Language Foundation Models
Unlike the existing image-text similarity objective which only categorizes matched pairs as similar and unmatched pairs as dissimilar, equivariance also requires similarity to vary faithfully according to the semantic changes.
Ranked #7 on
Visual Reasoning
on Winoground
Adaptive Human Matting for Dynamic Videos
The most recent efforts in video matting have focused on eliminating trimap dependency since trimap annotations are expensive and trimap-based methods are less adaptable for real-time applications.
Neural Voting Field for Camera-Space 3D Hand Pose Estimation
We present a unified framework for camera-space 3D hand pose estimation from a single RGB image based on 3D implicit representation.
Ranked #4 on
3D Hand Pose Estimation
on HO-3D
PaintSeg: Training-free Segmentation via Painting
The paper introduces PaintSeg, a new unsupervised method for segmenting objects without any training.
DisCo: Disentangled Control for Realistic Human Dance Generation
In this paper, we depart from the traditional paradigm of human motion transfer and emphasize two additional critical attributes for the synthesis of human dance content in social media contexts: (i) Generalizability: the model should be able to generalize beyond generic human viewpoints as well as unseen human subjects, backgrounds, and poses; (ii) Compositionality: it should allow for the seamless composition of seen/unseen subjects, backgrounds, and poses from different sources.
The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)
We hope that this preliminary exploration will inspire future research on the next-generation multimodal task formulation, new ways to exploit and enhance LMMs to solve real-world problems, and gaining better understanding of multimodal foundation models.
Completing Visual Objects via Bridging Generation and Segmentation
This paper presents a novel approach to object completion, with the primary goal of reconstructing a complete object from its partially visible components.
Idea2Img: Iterative Self-Refinement with GPT-4V(ision) for Automatic Image Design and Generation
We introduce ``Idea to Image,'' a system that enables multimodal iterative self-refinement with GPT-4V(ision) for automatic image design and generation.
MM-VID: Advancing Video Understanding with GPT-4V(ision)
We present MM-VID, an integrated system that harnesses the capabilities of GPT-4V, combined with specialized tools in vision, audio, and speech, to facilitate advanced video understanding.
MM-Narrator: Narrating Long-form Videos with Multimodal In-Context Learning
We present MM-Narrator, a novel system leveraging GPT-4 with multimodal in-context learning for the generation of audio descriptions (AD).
A Unified Gaussian Process for Branching and Nested Hyperparameter Optimization
To capture the conditional dependence between branching and nested parameters, a unified Bayesian optimization framework is proposed.
