Search Results for author:
Found 13 papers, 5 papers with code
SPAD : Spatially Aware Multiview Diffusers
We present SPAD, a novel approach for creating consistent multi-view images from text prompts or single images.
AToM: Amortized Text-to-Mesh using 2D Diffusion
We introduce Amortized Text-to-Mesh (AToM), a feed-forward text-to-mesh framework optimized across multiple text prompts simultaneously.
Virtual Pets: Animatable Animal Generation in 3D Scenes
Toward unlocking the potential of generative models in immersive 4D experiences, we introduce Virtual Pet, a novel pipeline to model realistic and diverse motions for target animal species within a 3D environment.
iNVS: Repurposing Diffusion Inpainters for Novel View Synthesis
Our approach focuses on maximizing the reuse of visible pixels from the source image.
CAMM: Building Category-Agnostic and Animatable 3D Models from Monocular Videos
Animating an object in 3D often requires an articulated structure, e. g. a kinematic chain or skeleton of the manipulated object with proper skinning weights, to obtain smooth movements and surface deformations.
Invertible Neural Skinning
Next, we combine PIN with a differentiable LBS module to build an expressive and end-to-end Invertible Neural Skinning (INS) pipeline.
Building Scalable Video Understanding Benchmarks through Sports
Our human studies indicate that ASAP can align videos and annotations with high fidelity, precision, and speed.
LaTeRF: Label and Text Driven Object Radiance Fields
In this paper we introduce LaTeRF, a method for extracting an object of interest from a scene given 2D images of the entire scene, known camera poses, a natural language description of the object, and a set of point-labels of object and non-object points in the input images.
Housekeep: Tidying Virtual Households using Commonsense Reasoning
Instead, the agent must learn from and is evaluated against human preferences of which objects belong where in a tidy house.
NarrationBot and InfoBot: A Hybrid System for Automated Video Description
To overcome the increasing gaps in video accessibility, we developed a hybrid system of two tools to 1) automatically generate descriptions for videos and 2) provide answers or additional descriptions in response to user queries on a video.
Contrast and Classify: Training Robust VQA Models
Recent Visual Question Answering (VQA) models have shown impressive performance on the VQA benchmark but remain sensitive to small linguistic variations in input questions.
Spatially Aware Multimodal Transformers for TextVQA
Further, each head in our multi-head self-attention layer focuses on a different subset of relations.
ICLR Reproducibility Challenge Report (Padam : Closing The Generalization Gap Of Adaptive Gradient Methods in Training Deep Neural Networks)
The authors try to address this problem by designing a new optimization algorithm that bridges the gap between the space of Adaptive Gradient algorithms and SGD with momentum.
