716 citations · 928 across the 12 of their papers we have counts for
13 papers
LooseControlVideo: Directorial Video Control using Spatial Blocking
Shariq Farooq Bhat, Niloy J. Mitra, Kalyan Sunkavalli
Precise 3D spatial orchestration in text-to-video generation remains a significant challenge, particularly for multi-object scenes where semantic layout and temporal dynamics are o…
CompoSE: Compositional Synthesis and Editing of 3D Shapes via Part-Aware Control
Habib Slim, Shariq Farooq Bhat, Mohamed Elhoseiny +2
Creating and editing high-quality 3D content remains a central challenge in computer graphics. We address this challenge by introducing CompoSE, a novel method for Compositional Sy…
PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimation
Zhenyu Li, Wenqing Cui, Shariq Farooq Bhat +1
While current high-resolution depth estimation methods achieve strong results, they often suffer from computational inefficiencies due to reliance on heavyweight models and multipl…
Amodal Depth Anything: Amodal Depth Estimation in the Wild
Zhenyu Li, Mykola Lavreniuk, Jian Shi +2
Amodal depth estimation aims to predict the depth of occluded (invisible) parts of objects in a scene. This task addresses the question of whether models can effectively perceive t…
PatchRefiner: Leveraging Synthetic Data for Real-Domain High-Resolution Monocular Metric Depth Estimation
Zhenyu Li, Shariq Farooq Bhat, Peter Wonka
This paper introduces PatchRefiner, an advanced framework for metric single image depth estimation aimed at high-resolution real-domain inputs. While depth estimation is crucial fo…
EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text Alignment
Mykola Lavreniuk, Shariq Farooq Bhat, Matthias Müller +1
This work presents the network architecture EVP (Enhanced Visual Perception). EVP builds on the previous work VPD which paved the way to use the Stable Diffusion network for comput…
LooseControl: Lifting ControlNet for Generalized Depth Conditioning
Shariq Farooq Bhat, Niloy J. Mitra, Peter Wonka
We present LooseControl to allow generalized depth conditioning for diffusion-based image generation. ControlNet, the SOTA for depth-conditioned image generation, produces remarkab…
PatchFusion: An End-to-End Tile-Based Framework for High-Resolution Monocular Metric Depth Estimation
Zhenyu Li, Shariq Farooq Bhat, Peter Wonka
Single image depth estimation is a foundational task in computer vision and generative modeling. However, prevailing depth estimation models grapple with accommodating the increasi…
LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts
Hanan Gani, Shariq Farooq Bhat, Muzammal Naseer +2
Diffusion-based generative models have significantly advanced text-to-image generation but encounter challenges when processing lengthy and intricate text prompts describing comple…
ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth
Shariq Farooq Bhat, Reiner Birkl, Diana Wofk +2
This paper tackles the problem of depth estimation from a single image. Existing work either focuses on generalization performance disregarding metric scale, i.e. relative depth es…
LocalBins: Improving Depth Estimation by Learning Local Distributions
Shariq Farooq Bhat, Ibraheem Alhashim, Peter Wonka
We propose a novel architecture for depth estimation from a single image. The architecture itself is based on the popular encoder-decoder architecture that is frequently used as a…
SketchGen: Generating Constrained CAD Sketches
Wamiq Reyaz Para, Shariq Farooq Bhat, Paul Guerrero +4
Computer-aided design (CAD) is the most widely used modeling approach for technical design. The typical starting point in these designs is 2D sketches which can later be extruded a…
AdaBins: Depth Estimation using Adaptive Bins
Shariq Farooq Bhat, Ibraheem Alhashim, Peter Wonka
We address the problem of estimating a high quality dense depth map from a single RGB input image. We start out with a baseline encoder-decoder convolutional neural network archite…