activity
20192026
most citedTDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion

17 citations · 33 across the 41 of their papers we have counts for

collaborators

44 papers

cs.CV2026

FurE: Efficient Instance-Specific 3D Fur Reconstruction without Animal-Fur Datasets

Srinjay Sarkar, Prakhar Kaushik, Soumava Paul +1

Realistic and editable animal fur reconstruction from multi-view images is challenging due to fine-scale detail, self-occlusion and obfuscation, and, unlike human hair, the lack of…

cs.CV2026

Technical Report on the CVPR 2026@AdvML Workshop Challenge

Tianyuan Zhang, Zonglei Jing, Jiangfan Liu +47

Vision-language agents (VLAs) are increasingly used to interpret complex driving scenes and support safety-critical reasoning. This report presents the CVPR 2026@AdvML Workshop Cha…

cs.CV2026

RATS! Patches Talk Through Registers: Emergent Parts in Register Attention Transformers

Timing Yang, Predrag Neskovic, Jansen Seheult +4

When humans see a bird, they recognize far more than just "bird" -- they see a head, wings, and talons, a structured assembly of reusable parts that can be identified across every…

cs.CV2026

SEMAGIC: Learning Semantically Consistent Deformable 3D Representations from In-the-Wild Images

Sky Cen, Wufei Ma, Guofeng Zhang +2

Learning deformable 3D object models from single-view in-the-wild images has enabled impressive 3D shape reconstruction without supervision. However, it remains unclear whether the…

cs.CV2026

Can These Views Be One Scene? Evaluating Multiview 3D Consistency when 3D Foundation Models Hallucinate

Soumava Paul, Prakhar Kaushik, Alan Yuille

Multiview 3D evaluation assumes that the images being scored are observations of one static 3D scene. This assumption can fail in NVS and sparse-view reconstruction: inputs or gene…

cs.AI2026

Meissa: Multi-modal Medical Agentic Intelligence

Yixiong Chen, Xinyi Bai, Yue Pan +2

Multi-modal large language models (MM-LLMs) have shown strong performance in medical image understanding and clinical reasoning. Recent medical agent systems extend them with tool…

cs.CV2026

HECTOR: Hybrid Editable Compositional Object References for Video Generation

Guofeng Zhang, Angtian Wang, Jacob Zhiyuan Fang +4

Real-world videos naturally portray complex interactions among distinct physical objects, effectively forming dynamic compositions of visual elements. However, most current video g…

cs.CV2026

Thinking with Spatial Code for Physical-World Video Reasoning

Jieneng Chen, Wenxin Ma, Ruisheng Yuan +3

We introduce Thinking with Spatial Code, a framework that transforms RGB video into explicit, temporally coherent 3D representations for physical-world visual question answering. W…

cs.LG2026

Shared LoRA Subspaces for almost Strict Continual Learning

Prakhar Kaushik, Ankit Vaidya, Shravan Chaudhari +2

Adapting large pretrained models to new tasks efficiently and continually is crucial for real-world deployment but remains challenging due to catastrophic forgetting and the high c…

cs.CV2026

Name That Part: 3D Part Segmentation and Naming

Soumava Paul, Prakhar Kaushik, Ankit Vaidya +2

We address semantic 3D part segmentation: decomposing objects into parts with meaningful names. While datasets exist with part annotations, their definitions are inconsistent acros…

cs.CV2025

Differences That Matter: Auditing Models for Capability Gap Discovery and Rectification

Qihao Liu, Chengzhi Mao, Yaojie Liu +2

Conventional evaluation methods for multimodal LLMs (MLLMs) lack interpretability and are often insufficient to fully disclose significant capability gaps across models. To address…

cs.LG2025

The Universal Weight Subspace Hypothesis

Prakhar Kaushik, Shravan Chaudhari, Ankit Vaidya +2

We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the first large-scale empirical evidence…

cs.AI2025

Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning

Qihao Liu, Luoxin Ye, Wufei Ma +2

Large language models (LLMs) with explicit reasoning capabilities excel at mathematical reasoning yet still commit process errors, such as incorrect calculations, brittle logic, an…

cs.CV2025

Perceptual Taxonomy: Evaluating and Guiding Hierarchical Scene Reasoning in Vision-Language Models

Jonathan Lee, Xingrui Wang, Jiawei Peng +9

We propose Perceptual Taxonomy, a structured process of scene understanding that first recognizes objects and their spatial configurations, then infers task-relevant properties suc…

cs.CV2025

TriDiff-4D: Fast 4D Generation through Diffusion-based Triplane Re-posing

Eddie Pokming Sheung, Qihao Liu, Wufei Ma +3

With the increasing demand for 3D animation, generating high-fidelity, controllable 4D avatars from textual descriptions remains a significant challenge. Despite notable efforts in…

cs.CV2025

TGT: Text-Grounded Trajectories for Locally Controlled Video Generation

Guofeng Zhang, Angtian Wang, Jacob Zhiyuan Fang +8

Text-to-video generation has advanced rapidly in visual fidelity, whereas standard methods still have limited ability to control the subject composition of generated scenes. Prior…

cs.RO2025

PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation

Yifan Yin, Zhengtao Han, Shivam Aarya +6

Fine-grained robot manipulation, such as lifting and rotating a bottle to display the label on the cap, requires robust reasoning about object parts and their relationships with in…

cs.CV2025

SpatialLLM: A Compound 3D-Informed Design towards Spatially-Intelligent Large Multimodal Models

Wufei Ma, Luoxin Ye, Celso M de Melo +2

Humans naturally understand 3D spatial relationships, enabling complex reasoning like predicting collisions of vehicles from different directions. Current large multimodal models (…

cs.CV2025

SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoning

Wufei Ma, Yu-Cheng Chou, Qihao Liu +4

Despite recent advances on multi-modal models, 3D spatial reasoning remains a challenging task for state-of-the-art open-source and proprietary models. Recent studies explore data-…

cs.CV2025

DINeMo: Learning Neural Mesh Models with no 3D Annotations

Weijie Guo, Guofeng Zhang, Wufei Ma +1

Category-level 3D/6D pose estimation is a crucial step towards comprehensive 3D scene understanding, which would enable a broad range of applications in robotics and embodied AI. R…

cs.LG2025

EigenLoRAx: Recycling Adapters to Find Principal Subspaces for Resource-Efficient Adaptation and Inference

Prakhar Kaushik, Ankit Vaidya, Shravan Chaudhari +1

The rapid growth of large models has raised concerns about their environmental impact and equity in accessibility due to significant computational costs. Low-Rank Adapters (LoRA) o…

cs.CV2024★ 1 cited

Flowing from Words to Pixels: A Noise-Free Framework for Cross-Modality Evolution

Qihao Liu, Xi Yin, Alan Yuille +2

Diffusion models, and their generalization, flow matching, have had a remarkable impact on the field of media generation. Here, the conventional approach is to learn the complex ma…

cs.CV2024

3DSRBench: A Comprehensive 3D Spatial Reasoning Benchmark

Wufei Ma, Haoyu Chen, Guofeng Zhang +4

3D spatial reasoning is the ability to analyze and interpret the positions, orientations, and spatial relationships of objects within the 3D space. This allows models to develop a…

cs.CV2024

Gaussian Scenes: Pose-Free Sparse-View Scene Reconstruction using Depth-Enhanced Diffusion Priors

Soumava Paul, Prakhar Kaushik, Alan Yuille

In this work, we introduce a generative approach for pose-free (without camera parameters) reconstruction of 360 scenes from a sparse set of 2D images. Pose-free scene reconstructi…